UCL Institute for Risk and Disaster Reduction



lRDR postgraduate programmes are based on core taught institute, programme and skills modules. These vary between programmes so please check the individual programme information to find out which modules comprise the different programmes.

Availability of modules

This module list is indicative and we cannot guarantee availability of modules, especially those in other departments. You should check the UCL Module Directory for the full list of modules for this academic year. We will endeavour to communicate any changes made during the year.

For undergraduate modules, please see the programme page or the UCL Module Catalogue.

IRDR Core Taught Modules:

These modules are compulsory for all our Master's programmes:

    IRDR0015 - Integrating Science into Risk and Disaster Reduction

    Risk, Hazard, Vulnerability, Disaster, Natural disaster, Risk modelling, Catastrophe model, Insurance, Mitigation, Risk reduction.

    Module Tutor: Dr Joanna Faure Walker (2019-2020 Dr Bayes Ahmed)

    Module code: IRDR0015, 15 credits

    Department: IRDR

    This module is intended to meet the growing and recognised need that scientific and other technical knowledge must become more integrated in a systematic way into disaster risk reduction strategies. The aims of the module therefore are: (i) to make students aware of the role science has to play in informing and improving disaster risk reduction strategies, and (ii) to equip students with the skills and knowledge enabling them to solve complex problems in disaster risk reduction through engagement with scientific knowledge, methods, data and expertise.

    The module will consider the following topics:

    • Overview of approaches to disaster risk reduction
    • Behavioural biases
    • Quantitative risk assessment
    • Dealing with uncertainty, including acceptable levels of risk and uncertainty
    • Catastrophe modelling
    • The role of the insurance industry in risk and disaster reduction
    • Warning, evacuation and shelter
    • Methodologies for individual and group decision-making
    • The roles of scientific evidence, scenario development and horizon scanning in responsible decision-making
    • Science and accountability
    • Science and policy
    • The nature and distribution of risk and disasters, including the temporal and spatial scales and the acute and chronic dimensions
    • Mitigation methods and early warning systems
    • How disaster risk may evolve in the future and how science and technology may be able to improve preparedness
    • The pressures in different sectors that limit the application of science in disaster risk reduction
    • Communication of complex issues to wide and varied audiences that will have different objectives with regard to issues and solutions

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    IRDR0002 - Fundamentals of Emergency and Crisis Planning and Management

    Emergency, Crisis, Disaster, Emergency plan, Business continuity planning, Response, Recovery

    Module Tutor: Professor David Alexander (2019-2020 Dr Gianluca Pescaroli)

    Module code: IRDR0002, 15 credits

    Department: IRDR

    This module provides a comprehensive introduction to emergency planning and management for crises, major incidents and disasters. It covers the standards, principles, templates and research methods involved. Students will learn about the techniques used to assess vulnerability, risk and impact, plan for emergency response, and create a system that enables events to be managed effectively and efficiently. They will learn about the systems used in emergency response and the dynamics of emergency situations. Students will learn how to create, utilise and maintain emergency plans in both generic terms and for specific sectors. They will learn how to research, write, implement and verify plans, and how to mount a successful emergency response coordination operation. Students will learn to construct scenarios for different contingencies and use their outcomes as vital ingredients in plans. Students will be encouraged to treat planning as a process rather than an outcome. They will learn about the logistical, organisational, administrative, policy and legal contexts of emergency and crisis planning and management, and how to communicate effectively in emergencies. Examples will be drawn from contemporary practice, including the current emergency.
    The module will cover the following topics:

    Evolution of emergency management; disaster myths and misassumptions; vulnerability, risk and resilience; urban hazards and megacities; scenario methodology; case-study methods; cascading disasters; operational capability and evaluation of civil protection systems; standards; Internet resources and professional associations; emergency planning overview and plan structure; emergency management; command systems; emergency operations centres; interoperability; warning and evacuation; policy and legal aspects of emergency response; urban search and rescue; helicopters in emergency work; emergency logistics and feeding; mass media communication and the role of the spokesperson; social media; simulation exercises.

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    IRDR Taught Skills Modules:

    Taught skills modules available in all our programmes (see individual masters programme pages to find out which are compulsory / optional):

      IRDR0004 - Data Analysis and Interpretation

      Module Tutor: Dr. Patty Kostkova

      Module code: IRDR0004, 15 credits

      Department: IRDR

      This module aims to equip students with tools for analyzing qualitative, quantitative and spatial data relating to risk and disaster reduction and public health emergencies including interviews, surveys and mapping.

      As a student on this module you will learn basic statistical methods for survey design, and statistical and qualitative techniques for data analysis. You will gain hands-on programming experience in order to equip you with the tools to conduct independent research and analysis work in risk and disaster reduction. This will include analyzing data using an example programming language. Additional computing skills will be gained through an introduction to Geographical Information Systems (GIS) and Remote Sensitng (RS) which provides both scientific and practical knowledge of industry-standard software used to analyse geographical data.

      Through lectures, seminars, class discussions and computer exercises featuring examples relating to disaster risk reduction, you will learn:

      • Planning and designing data collection
        - Introduction to statistics
        - Statistical distributions
        - Samples and Populations 
      • Qualitative data analysis
        - Deconstructing responses to surveys, interviews and questionnaires
        - Software for analysing social science data 
      • Quantitative data analysis
        - Probabilities
        - Hypothesis testing (parametric and non-parametric)
        - Linear regression (single and multi variable)
      • Introduction to Programming
        - Pseudo code
        - Programming for practical data analysis 
      • Spatial data analysis through Geographical Information Systems (GIS) and Remote Sensing (RS)
        - Scientific and practical knowledge of industry-standard software to analyse geographical data

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      IRDR0005 - Practice and Appraisal of Research

      Module Tutor: Professor David Alexander 

      Module code: IRDR0005, 15 credits

      Department: IRDR

      This module aims to equip students with the tools required to plan, implement, present and evaluate primary research relating to risk and disaster reduction.

      As a student on this module you will learn about the research project chain including the process for proposing research ideas, acquiring funding and approval for such work, logistical planning of fieldwork for both research and emergency response, designing your data collection strategy, practical techniques for fieldwork, presenting your own findings and placing them in context by being able to critique the work of others.

      Through lectures, seminars, class discussions and exercises featuring examples relating to disaster risk reduction, and practical fieldwork experience  you will learn:

      • How to evaluate research from presentations and papers

      How to write effective research, consultancy and funding proposals
      How to formulate the research question
      How to structure a literature review in a proposal
      How to assess resource needs
      Apportioning time and resources in a project
      What makes proposals attractive - and pitfalls to avoid

      • Research Presentation

      Audience-appropriate research communication through talks, papers, reports and posters

      • Effective data collection

      How quantitative and qualitative data research differs
      How to conduct interviews
      How to write surveys 
      How to plan questionnaires

      • Fieldwork requirements

      Risk Assessment
      Fieldwork Ethics

      • Responsive fieldwork planning

      Participate in a simulated real-time event scenario run by practioners:
      Real-time experience of logistical decision making in response to a disaster, led by current practitioners.
      What kind of decisions need to be made, how the decision process works, constraints imposed by lack of detailed information and the need for urgency, the need to balance planning and adaptability in response to the developing situation, and the importance of team work in a high-pressure environment.

      • Conducting Fieldwork

      Participate in a residential fieldtrip in Southwest England:
      Hands-on experience in collecting and recording quantitative and qualitative data in the field
      An appreciation of different perspectives from professionals in both the private and public sector assessing risks posed to the UK
      Practice delivering evidence-based arguments within a structured debate about risk using various types of data

      Further IRDR Taught Modules:

      These module can be compulsory or optional for different masters programmes and are not available across all programmes:

      IRDR0001 - Natural and Anthropogenic Hazards and Vulnerability

      Hazard, Vulnerability, Resilience, Natural hazard, Anthropogenic Hazard, Extra-terrestrial Hazard, Geological hazard, Geophysical hazard, Meteorological hazard, Risk, Disaster, Natural disaster, multi-hazard, Earthquake, Tsunami, Landslide, Volcano, Severe storm, Hurricane, Cyclone, Tornado, Flood, Drought, Terrorism, Building vulnerability

      Module Tutor: Dr Joanna Faure Walker (2019-2020 Dr Punam Yadav)

      Module code: IRDR0001, 15 credits

      Department: IRDR

      This module is intended to meet the growing and recognized need for those in the field of risk and disaster reduction to follow a multi-hazard approach. Therefore, those in this field need to have an understanding of the hazards and vulnerability from a wide range of both natural and anthropogenic hazards. This module also intends to meet the need to understand a hazard in context with its vulnerability in order to help bridge the gap between studying the causes of a hazard and its implications for individuals and society, policy makers, and industry.

      This module will provide a basic scientific knowledge for a number of individual natural and anthropogenic hazards and their vulnerability, likely to include the following: Extra terrestrial hazards such as Extra-Terrestrial Impactors and Solar Flares, Geophysical Hazards such as Earthquakes, Tsunami, Landslides, and Volcanoes, Meteorological events such as Windstorms, Tornadoes, Flood, and Drought, and Anthropogenic Hazards such as Water (availability and contamination), Pandemics, Terrorism, Cyber-crime, Crowding, Health.

      The student will learn to compare and contrast the different severity imposed by such natural and anthropogenic hazards, with specific reference to their frequency, geographical extent, economic vulnerability, human vulnerability, our ability to forecast or predict them and the scientific limits on these.

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      IRDR0003 - Advanced Emergency and Crisis Planning and Management

      Emergency, Crisis, Disaster, Emergency management, Business continuity management, Response, Recovery

      Module Tutor: Professor David Alexander

      Module code: IRDR0003, 15 credits

      Department: IRDR

      Emergency and disaster planning and management are set to become a fully-fledged profession. They require practitioners to coordinate complex operations that involve many different kinds of expert and widely diverse problems that must be solved rapidly and efficiently. This module will deal systematically with specialised emergency planning and management, as applied to different sectors. These include cultural heritage, the care and protection of disabled people, the medical and industrial sectors, and planning to keep mass gatherings safe. Counter-terrorism will be examined in terms of both general practice and the lessons of past events. Humanitarian emergencies will be discussed with respect to international policy, planning and management. The psychological effects of major emergencies upon people who manage and respond to them will be investigated. Ample use will be made of case histories and scenario-based classroom discussions and exercises.

      The module will cover the following topics:

      State of the art in emergency planning and management; pandemics and epidemiology; death and injury in disasters; medical emergency management; critical infrastructure and wide-area power failure; industrial emergencies and hazardous materials transportation; cultural heritage protection; safety of mass gatherings; response to terrorism and CBRN incidents; people with disabilities in emergency situations; disaster management in developing countries; migration and refugee emergencies; civil-military cooperation; shelter, recovery and reconstruction; adapting response and planning to systemic risk; the Sendai Framework for Disaster Risk Reduction; stress and the emergency manager; examples of emergency planning and management problems from the UK, Japan and the world.

        IRDR0006 - Conflict, Humanitarianism and Disaster Risk Reduction

        Module tutor: Dr. Ilan Kelman

        Module code: IRDR0006, 15 credits

        Department: IRDR

        Conflict continues to take an excessive toll on humanity with humanitarianism for all forms of disasters continuing to be an important sector. Despite many notable successes, why are disaster risk reduction and conflict resolution efforts not solving all the challenges? 

        This module aims to help students understand the importance of a disaster risk reduction perspective for conflict and humanitarianism, to experience how communication in such situations is made to and from various stakeholders, to discuss field sites with disaster risk, and to improve their own awareness in terms of identifying which of their own skills they need to develop to adequately deal with conflict and humanitarian situations from a disaster risk reduction perspective.

        The lectures, assessments, and seminars will meet the growing and recognised need for those in the field of risk and disaster reduction to understand better the meanings and contexts of conflict and humanitarian settings and how to take a disaster risk reduction perspective of conflict and humanitarianism.

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        IRDR0008 - Catastrophe Risk Modelling

        Risk, Hazard, Vulnerability, Disaster, Risk modelling, Catastrophe model, Insurance.

        Module Tutor: Dr Joanna Faure Walker (2019-2020 Dr Carmine Galasso

        Module code: IRDR0008, 15 credits

        Department: IRDR

        This module aims to provide the student with an understanding of the science and engineering underlying catastrophe models. It will further discuss catastrophe modelling in the context of risk transfer in industry and future possibilities for building resilience. An industry-focussed module, this module is taught by a range of guest lecturers from within industry and UCL lecturers who have industrial experience working within the Catastrophe Modelling industry.

        Students will be required to undertake quantitative calculations and analysis developing and using basic code as part of the assessment.

        In this module, the following topics will be covered: 

        • An introduction to catastrophe modelling and how they can be used for building resilience.
        • Probabilities and statistics - the role of uncertainties, probability, and Monte Carlo simulation in Catastrophe models
        • Hazard modelling including examples of earthquake, wind and flood
        • Exposure Modelling and its challenges
        • Fragility and Vulnerability Modelling with a focus on earthquake, wind and storm surge modelling
        • Financial losses
        • Application of catastrophe risk models for pre and/or post-event loss modelling and real-time scenarios
        • Appraising and selecting current models 
        • The challenges and issues in application of catastrophe models in developing countries.

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        IRDR0009 - Digital Health: Epidemics and Emergencies in the Era of Big Data

        Public health, global health, big data, serious games, computer science, disaster surveillance

        Module Tutor: Dr Patty Kostkova

        Module code: IRDR0009, 15 credits

        Department: IRDR

        This module will introduce students to the key concepts of digital public health. It will cover the underlying computer science principles including knowledge management, semantic modelling, international disaster surveillance IT systems; early warning and response to disease outbreaks and emergencies, social media and serious games for public health interventions and behaviour change. Students will become familiar with the fundamental principles of public health, global health, disease surveillance, epidemic intelligence, emergencies, public health  behaviour change interventions, and risk communication.  This module is aimed at postgraduate students with a science degree or medical sciences degree with interests in new technologies for public and global health, emergencies and big data challenges. This will enable students  to apply for jobs and placements at international public health agencies and NGOs (e.g., European Centre for Disease Prevention and Control, MSF, Save the Children, Joint Research Centre, WHO, etc).

        This module is expected to feature senior guest lecturers from international public health and disaster organisations.

        This module is suitable for students from all backgrounds, however, students with CS/IT, science, GIS backgrounds would find it particularity appropriate. The module does not require programming skills as a prerequisite and assumes very basic statistical skills. The assessment projects will be allocated to students drawing from their skills and backgrounds. Please see me if you want to discuss the skills needed to take this module.

        It will apply problem-orientated learning methods (POL) to:

        • introduce public health, field epidemiology, and global health concepts
        • present the key technological systems underpinning public health surveillance, early warning, and response to outbreaks and epidemics
        • understanding challenges and opportunities created by new technologies, social media, mobile systems
        • apply the principles in the practice on case studies and on technologies and/or try interactive hands-on approaches
        • apply new knowledge on an interdisciplinary project of choice gaining in-depth practical experience with the subject. The project should form a substantial part of a student's application for a placement in the host public health institution.  
        IRDR0010 - Advanced Hazards

        Risk, earthquake, seismology, statistical modelling, numerical modelling, earthquake science, seismic risk assessment

        Module Tutor: Dr Katerina Stavrianaki, Prof Peter Sammonds

        Module code: IRDR0010, 15 credits

        Department: IRDR

        The module aims to take a modelling and statistical approach to geophysical risks. Students will understand statistical modelling and observational approaches to geophysical events such as earthquakes. Students should understand the disaster chain from hazard to risk. You will gain the knowledge and skills necessary to analyse disaster-related risks posed using statistical risk analysis techniques. You will understand the successes and limitations of statistical approaches to risk assessment and the impact this has on our current mitigation strategies including risk transfer mechanisms.

        IRDR0012 - Independent Project

        Module Tutor: Dr. Punam Yadav 

        60 credits

        Department: IRDR

        The independent project provides an opportunity for the student to focus on a particular research question that interests you. An independent project must represent original research. The project may involve collecting and analysing new data, analysing existing data, or presenting a new theory. Students have the option to propose their own master's project topic and discuss this with a potential supervisor or select one from a list of suggested projects.

        See module in UCL Module Catalogue

        IRDR0016 - Gender, Disaster and Conflict

        Key words:  
        Gender responsiveness, structural vulnerabilities, sexual minorities, violence, disaster, conflict, peace, policy, gender theory, intersectionality, LGBTQI, climate change, migration, IDPs

        Module Tutor: Dr. Punam Yadav 

        15 credits

        Department: IRDR

        This module offered so much more than I was expecting, and I am sad to leave it behind. The seminars never failed to disappoint; always highly informative and challenging and I enjoyed the class discussions. The involvement of guest lecturers brought diversity to the syllabus. Punam is very good in encouraging discussion and comment around difficult topics, and she is skilful in managing positive group participation. I find this unique amongst the modules I have taken over the course of my Masters, and would encourage anyone to take this thought-provoking module (student’s feedback from batch 2020-2021).
        Our experience of any crisis is largely determined by gendered power relations and unequal social structures. Women, men and sexual minorities are impacted differently in conflict and disaster. In general, more men are likely to die in conflict, whereas more women die in disaster. This is due to their gender roles, social expectations and unequal power relations. Women are faced with different forms of violence in conflict and disaster, as they are in the everyday. Hence, this module aims to advance students’ understanding around differential gendered impacts of conflict and disaster, and gender responsiveness in Disaster Risk Reduction (DRR), by analysing the structural causes of vulnerabilities and marginalisation. 
        The module is organized around three key aspects: theoretical debates in three core domains: gender, disaster and conflict; case studies examining the real-life experiences of people living in conflict and disaster vulnerable countries and contexts; and policies (from the global to the local) and practices (where gender inequality, and resistances to it, are manifest). All classes are interactive, and students are encouraged to engage in discussion and debate, and to share their own experiences and knowledge, throughout all sessions.
        As a student on this module, you will learn about the following topics through lectures, key readings, and class discussions: the basic concepts of gender and gender theories; masculinities and femininities; the significance and the relevance of gender to DRR and humanitarian crisis; the continuum of violence, including GBV; the relationships between gender, conflict and disaster; gender and intersectionality; LGBTQI; gender and DRR policies and frameworks; forced migration and internal displacement. After the completion of this module, you will have a better understanding of gender responsive approaches to DRR and humanitarian crises.
        We will use a mix of lectures, activities, films, critical reading and discussion. We also encourage you to get involved with the IRDR Centre for Gender and Disaster and other relevant networks; and we will provide an overview of these opportunities in the first session.
        This module received excellent students’ feedback.

        This was module was my favourite module of my Masters course. The well-structured material, coupled with the seminar interactive sessions made this module a great learning experience. The small class size made contributing to discussions easy and the group breakout discussions worked really well. I also thought the critical reading and blog assessments were really interesting (Student’s feedback from batch 2020-2021).

        The module has completely changed how I now view and analyse disasters. I started the Gender, Disaster and Conflict module, with little understanding of gender studies. However, not only have I gained knowledge in gender theory, and its applications within the disaster and conflict context, but I have also had the opportunity to participate in discussions with leading academics and practitioners, that have undertaken incredibly meaningful research. Without doubt I will take this new perspective forward with me in my future work and career. Emma, MSc student 2019-2020. 

        I thought adding conflict into the module was an excellent addition to what is mainly a disaster focused course. By incorporating gender with disaster and conflicts, it allowed for wider discussions on topics which I have never previously studied or had the chance to study, especially by professionals in the field. Olivia, MSc student, 2019-2020 

        Recommended Readings 

        1.    RW Connell and Rebecca Pearse (2015). Gender: In world perspective. Polity Press
        2.    Judith Butler (2006). Gender Trouble: feminism and the subervision of identity. Routledge
        3.    Patricia Hill Collins and Sirma Bilge (2016). Intersectionality. Polity press 
        4.    Punam Yadav (2020). Can women benefit from war? Women’s agency in conflict and post-conflict contexts. Journal of Peace Research, vol 58 (3): 449-461 https://doi.org/10.1177/0022343320905619 
        5.    Gaillard, J.C., Gorman-Murray, A. and Fordham, M. (2017) Sexual and gender minorities in disaster, Gender, Place and Culture, Gender, Place and Culture 24 (1), pp. 18-26.
        6.    R W Connell (2020): Masculinities, University of California Press 
        7.    Carol Cohn (2013) (ed.). Gender and Wars. Polity press
        8.    Punam Yadav and Denise Horn (2021). “Continuum of violence: feminist peace research and gender-based violence”, in Tarja Väyrynen, Swati Parashar, Élise Féron, and Catia Cecilia Confortini (eds.) Routledge Handbook of Feminist Peace Research. Abingdon, Oxon: Routledge https://www.taylorfrancis.com/chapters/continuums-violence-punam-yadav-d...


        IRDR0017 - Business Continuity Management and Organisational Resilience

        Managing operations, supply chain distributions

        Module Tutor: Dr. Gianluca Pescaroli

        15 credits

        Department: IRDR

        This module aims to give the understanding of Business Continuity Management (BCM) as an essential process for enhancing organisational resilience in the public and private sectors. It aims to enable students to integrate resilience in “business as usual” management, supporting them in understanding of how developing the analysis of requirements, design and implement solutions, validating the objectives and procedures put in place. The students will be able to critically analyse the challenges for organizational resilience in different contexts, building up on good practices and procedures shared during the course. Finally, they should also be able to recall the tools explained in the course, such as threat and risk analysis, and be familiar with the collaborative approach required to implement them in a comprehensive process. 

        The module consists of an overview of Business Continuity Management (BCM) and its application for building organizational resilience, including:

        • The BCM Lifecycle
        • ISO standards
         The core lectures will be supported by group exercises to give familiarity with BCM as a process, while a set of guest speakers will share their experiences. The participants are encouraged to actively contribute to the lessons.  
        • Analysis of requirements; 
        • Design and implementation of solutions;
        • Validation of the objectives and procedures;
        • Business impact analysis and threat and risk analysis;
        • Good practices for integrating BCM in “business as usual” management.

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        Additional Modules

        All IRDR masters-level modules are available on all programmes, either as compulsory or optional modules. In addition, the following modules taught across other departments at UCL are available on selected programmes.
        *Please note the availability of particular optional modules can vary and cannot be guaranteed.*

        Space Science, Environment and Satellite Missions

        Lecturers: Dr S. Matthews, Prof. A. Coates, Mr M. Whyndham

        Module: 15 credits

        Teaching Term: 1

        Department: UCL Department of Space and Climate Physics

        This module will give students an appreciation of the history of early spaceflight and examples of early space science satellites. Lectures will lead students to understand different space science fields, and will equip them with basic knowledge of the spacecraft environment, of spacecraft dynamics, rocket propulsion, spacecraft design and the essential spacecraft sub-systems; will inform them about space mission planning and space project management.

        Topics covered by the module:

        • Space science and other space applications - Brief history of early spaceflight to 1961. Examples of early space science satellites: Ariel 1, Orbiting Observatories, European programme. Brief outline descriptions of the following space science fields, with major related space science missions and discoveries: solar physics, space plasmas (solar wind and Earth's magnetosphere), solar system exploration (moons, planets, asteroids and comets), astrophysics from space, Earth observation from space (remote sensing).
        • The spacecraft environment - Earth's atmosphere, equation of hydrostatic equilibrium, measurements of density, atmospheric drag. The ionosphere and solar radiation, the trapped particle zone (radiation belts). The magnetosphere, the Sun and the solar wind.
        • Spacecraft dynamics - Orbits, trajectories and launching. The nature of satellite orbits and elementary orbit theory, perturbations. Rocket propulsion - the rocket equation, propellants and specific impulse, nozzle design, staging.
        • Mission objectives. Design concept and assessment of requirements. Proposal document - scientific justification, technical plan, management plan, cost, PA, interface document.
        • Funding application.
        • Project management - organogramme, work packages, schedule. PERT network, milestones, critical path, progress meetings, expenditure profiles and financial control.
        • Mission planning and operations, science planning, timelining, ground support
        Space Systems Engineering

        Module Tutors: Mr M.Whyndham, Prof. I. Hepburn

        Module: 15 credits

        Department: Space and Climate Physics


        The aim of this module is to provide an understanding of how a spacecraft operates from a technological perspective. This will necessitate exploring the physical, mathematical and engineering principles used in the operation of the major subsystems of a modern spacecraft. On completion of the module the student will be able to describe in some detail the major subsystems of a spacecraft, calculate the basis of operation of these, develop simple models of their functional scope and relate these to simple scientific or operational goals of space missions.

        Topics covered by the module:

        • Systems engineering lifecycle, structure and management of systems development projects and programmes, management of requirements and interfaces. Technology selection, development, insertion and trade-off.
        • Review of scientific spacecraft subsystems, with examples from modern space vehicles. Spacecraft and instrument design constraints and evolution - size, mass, geometry, power, apertures, thermal control, surface requirements, booms, e-m properties, command capability, data rate.
        • Mechanical sub-systems: the mechanical environment and design.
        • Electrical sub-systems: power sub-system and other electronic sub-systems, including analogue signal amplification and processing.
        • The spacecraft thermal environment and design considerations and methods. Cooling methods and refrigeration.
        • Attitude control and station keeping, and the basic technology of attitude sensors.
        • Quality management in the space domain, qualification and integration activities. Component, sub-assembly, instrument and spacecraft level tests. Vibration, temperature, vacuum, solar simulation tests. Configuration management.
        • Product assurance: approved parts and materials lists, cleanliness, testing, protection during shipping, documentation.
        • Commanding and data acquisition. Data relay satellites, ground stations, control centre requirements.
        • Digitised signal data, On-Board Data Handling (OBDH), telemetry and telecommanding, including encoding and command decoding, error detection and correction, RF satellite communications links and link budgets.
        Decision and Risk Statistics

        Module Tutor: tbc (Please contact Dr Katerina Stavrianaki k.stavrianaki@ucl.ac.uk for inquiries )

        Module: 15 credits

        Department: Statistics and IRDR

        This course aims to give an introduction to the statistical treatment of risk, the calculation of losses, and the theory of how to make optimal decisions based on such considerations. We begin with a review of statistical methods for estimating parameters of physical processes, and then show how these can be used to find the expected loss associated with different decisions, allowing choices to be made. Much of this course focuses on how to estimate the probability of extreme events occurring, for example high magnitude earthquakes, or large terrorist attacks. Additionally, we cover methods for detecting whether something important about a physical process has changed, so that risk computations can be updated in the light of new information.

        On successful completion of this course, a student should be able to understand measures of risk, find appropriate probability models for risky events, and check the validity of the underlying assumptions, understand Bayesian risk together with its theoretical assumptions, understand basic extreme value statistics, and understand basic time series modelling with structural change detection.

        Entrepreneurship: Theory and Practice

        This is UCL's principal Entrepreneurship course for students who are actively seeking to develop and test a new business idea. It is most relevant to  those who are considering forming their own business  but is also valuable for “intrapreneurs”  promoting new initiatives within existing organisations. 

        Through the study of existing high-potential ventures and the development of a business feasibility plan the course provides deep insights regarding critical success factors  (desirability feasibility and viability) along with strategies to attract and retain the necessary resources (personal, technical and finance) to launch a new venture. 

        In doing so the course seeks to develop the entrepreneurial skills, behaviours and attitudes that are essential for individuals seeking to create and capture value through innovative business activities.

        Decision and Risk Analysis

        Important business decisions cannot be left to intuition alone. We need to communicate the structure of our reasoning, defend it to adversarial challenges and make presentations that show we have done a thorough analysis. We also need to make sense out of various sources of data, organise the inputs of experts and colleagues, and use state-of-the-art tools to provide analytical support for our reasoning.

        The objective of this course is to equip you to be more effective in these tasks. You will develop skills in data analysis, structuring decisions, building decision models, risk assessment, decision making under uncertainty, recognising areas where business analysis can add value, selecting appropriate types of analyses and learn to apply them in a small scale, quick-turnaround fashion.

        This is a practical course, which uses state-of-the-art decision support software to illustrate how to apply the methodologies introduced. Therefore, the course consists of a mixture of lectures and computer workshops. The software used in the lectures and workshops is Microsoft Excel, with add-ins @Risk for simulation, PrecisionTree for decision analysis, and Solver for optimisation. To ensure your working knowledge of Excel, we require you to attend a workshop session in Excel in Term 1 and complete the necessary assignment prior to the start of the course.

        Mastering Entrepreneurship

        This course is designed to develop core enterprise skills whilst providing an insight into how individuals and organisations create and capture value through entrepreneurial activity. 

        It is intended to provide the skills and knowledge work more entrepreneurially in a range of entrepreneurial contexts including established businesses as well as new start-ups. 

        The course focusses on innovation in the design and development of  new products, processes and markets. In doing so it  seeks to develop an understanding of how  personal, technical and market  factors influence successful outcomes along with strategies to secure the resources to move from idea to action.

        Project, Programme and Portfolio Management

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        Influence and Negotiations

        Negotiation is the science of securing agreements between two or more interdependent parties, and it is a part of our everyday lives.

        The primary goal of this course is to provide students with the fundamentals of effective negotiation and communication through a series of group simulations, exercises, feedback, and debriefing sessions. Students will become equipped with a toolkit to address a range of contexts that call for negotiation skills. The experiential learning approach will guide students toward a better awareness and understanding of negotiation strategies and tactics that they can apply to real-world negotiations.

        The core concepts presented in the course will help them develop wiser decision-making strategies under pressure, a more systematic framework to prepare for and execute negotiations, and greater facility in approaches for creating and capturing value in negotiation.

        Space Data Systems and Processing

        Lecturers: Prof Sarah Matthews
        Department: Space and Climate Physics

        On successful completion of this module, students should have competence in understanding current applications of downstream data (in the areas specified below), finding and using space data, processing data products to acquire further scientific knowledge or make statements about the natural and human-made environments (mostly Earth’s, but not exclusively), combining data from many sources in support of such processes, stating limitations of given datasets, defining basic requirements for data systems (current and future).

        This is a short, intensive module, run over five weeks, with 6 hours of lectures on a specific topic, and delivered by a different lecturer, each week. The five topics are:

        1) Positioning

        Principles of positioning systems and practicalities. Applications (methods and uses): vehicles, ground transport in general, personal, navigation, metrology, asset management, security, defence services. Future developments and enhancements.

        2) Solar-Terrestrial Relationships

        Terrestrial applications, Earth magnetosphere and space weather, solar cycle and activity in general (e.g. CMEs), NOAA reports, end users (e.g. aircraft and spacecraft operators, power lines on the ground). Science of space weather and solar-terrestrial relationships, possible connection between solar activity and Earth’s climate.

        3) Telecommunications

        Communications and broadcast services and applications, an introduction; basic principles of space communications; data formatting and encryption; data security; orbits and coverage; communication bands, their application and allocation; radio-amateur satellites; National Space Technology Roadmap for telecoms; an anatomy of a telecoms satellite; partnerships and collaborators in a satellite TV broadcast.

        4) Earth Observations (EO) and Global Change

        Different purposes of EO, of which climate is one; weather monitoring and forecasting, defense, agriculture, natural resource exploitation, geographical science, disaster monitoring and predicting, urban and territory planning, climate and global change, importance of remote sensing.

        5) Astronomy

        Statistics of photon collecting and data reduction, time series analysis and applications to recent space observations.

        Science Policy in an Era of Risk and Uncertainty


        Lecturer: Dr Carina Fearnley
        Department: Science and Technology Studies

        This module aims to bring together key thinkers, debates, and cutting-edge research on how society has, currently, and may engage with environmental uncertainty and risk. In addition a number of relevant research methodologies and interdisciplinary skills will be applied in a series of practicals to demonstrate the challenges we face in these large, global complex problems. This module aims to discuss the challenges of integrating interdisciplinary data sets, and the role of more deliberative and participatory engagement for stakeholders. The module will consist of lectures and seminars and will adopt a problem-based learning approach, whereby a topic of interest can be selected so to apply the knowledge learnt to the selected case study. Contemporary case studies will be explored throughout the course.

        Introduction to statistical data science


        Lecturer: Dr Francois-Xavier Briol
        Department: Statistical Science

        This module aims to provide a general background on fundamental statistical methods and applications in data science. It is intended for students registered on certain taught postgraduate degree programmes offered by the Department of Statistical Science, or jointly with other departments.

        Objectives - On successful completion of the module, students should have an understanding of the fundamental aspects of probability and statistics sufficient to follow other taught postgraduate level modules in Statistical Science. Students should also be equipped to lead basic data analysis projects in industry and research. The module will teach students: how to use probability as a language to express uncertainty, ways of visualizing and preparing data for statistical analysis, estimation techniques in the context of applied data analysis problems, the role of algorithms in the computation of estimators, how to express uncertainty in estimation via confidence intervals and hypothesis testing, predictive analysis from the point of view of regression.

        Applications - The statistical methods introduced in STAT0032 are very general, and they are used in almost all areas in which statistics is applied. In the module, we will discuss applications in the context of business, social sciences, and biology, among others.

        Content - Exploratory data analysis: basic visualisation for data preparation and modelling strategy. Review of probability models, in the context of the different statistical methods discussed in the module. Hypothesis testing and confidence intervals: methods for assessing the uncertainty in the analysis. Regression: linear and non-linear methods for explaining outcomes. Point estimation, maximum likelihood and basic optimization: fitting generic statistical models. Dimensionality reduction: explaining the variability in datasets using fewer dimensions.