4-year ACED PhD programme in cancer early detection at UCL.
The deadline for applications is 5pm Monday 4th November 2024.
The International Alliance for Cancer Early Detection (ACED) is a partnership between Cancer Research UK, University College London, the Canary Center at Stanford University, the University of Cambridge, the Knight Cancer Institute at OHSU, the University of Manchester, and the German Cancer Research Center DKFZ.
Earlier detection of cancer offers the greatest opportunity to deliver improvements in successful outcomes for patients. By diagnosing cancer earlier, it is easier to treat, causing less suffering to patients and could save lives.
ACED has the bold ambition to accelerate and revolutionise research in the in the early detection of cancers by uniting world leading researchers to bring together the best early detection science across the UK and US.
We are seeking candidates with an outstanding academic record (first class Bachelor's or Master’s degree or equivalent) in a discipline relevant to early detection research, including but not limited to: biochemistry/molecular biology, biophysics, computer science, engineering, epidemiology, public health, physics, mathematics, medicine.
Details of the Studentship
ACED is committed to training the next generation of early detection scientists and providing a supportive and flexible training environment. The ACED PhD programme provides unique support by offering a multi-disciplinary and multi-institutional approach to training.
The first year of the 4-year programme allows the students to develop their project with their UCL supervisor as well as training in different disciplines relevant to cancer early detection. This will be followed by a 3-year research project.
ACED PhD students will also benefit from:
- Regular programme of virtual events - including research seminars and Masterclasses from researchers across the ACED Centres.
- Early Detection Summer School.
- Annual Early Detection of Cancer Conference.
- UCL Doctoral Skills Development Programme providing the opportunity to expand your research and transferable skills in order to support your research, professional development and employability.
Funding
The funding for this studentship includes tuition fees at the UK home rate only (funding will not cover international fees). For eligible students, the studentship will provide running expenses and an annual maintenance stipend of £23,000 funded by Cancer Research UK for up to 4 years, subject to satisfactory progress.
Eligibility
Due to funding restrictions, we will only be able to offer studentships to candidates that have UK “home” tuition fee status (i.e. UK National or have EU “pre-settled” or “settled” status), self-funding of the international portion of the tuition fee will not be eligible. For more information on home tuition fee status please visit the UKCISA website. Candidates must meet the UCL entry requirements.
Supervisor arrangements
The successful student will select their UCL Principal Supervisor in a subject area of their choice from an approved list of UCL ACED PhD Supervisors. The Principal Supervisor and student will co-develop the PhD research project during the first year of the Programme, including selecting a suitable co-supervisor with complementary expertise to enhance the project from another ACED Member Centre.
UCL ACED PhD Supervisors 2025
Name | Research Interests in early detection | Research question to form the basis of PhD project |
Screening for gynaecological cancers (ovarian, endometrial, cervical). | Ovarian cancer usually presents at advanced stage when survival is poor. Screening has not shown mortality benefit, despite the UKCTOCS trial demonstrating early-stage cancer detection using CA125-algorithm approach. Biomarkers for premalignant STIC lesions are lacking. How would you discover novel biomarkers for ovarian cancer to inform future prospective studies/trials? | |
Research Department of Oncology, UCL Cancer Institute | Lung Cancer Genomics and the lung cancer tumour microenvironment. Investigator in the NIMBLE (NCT05432739) early lung cancer detection study. | What is the role of clonal haematopoiesis of indeterminate potential (CHIP) in the immunosurveillance of early lung cancer and what is the utility of CHIP as a marker of lung cancer risk? |
Machine learning, prostate cancer, imaging, surgery | How can we improve the prediction, detection and staging of prostate cancer on medical imaging? | |
Urology, Division of Surgery and Interventional Science | My work (PRECISION trial, NEJM) has led to the first major change in 30 years in the way that we diagnose prostate cancer, introducing MRI into the pathway. I am interested in optimising the way we use MRI, exploring novel technology such as PSMA PET and using artificial intelligence. | How can we use artificial intelligence, MRI and PSMA PET to improve the way that we diagnose prostate cancer? |
Research Department of Targeted Intervention, Division of Surgery and Interventional Science | We have an established program exploring the use of artificial intelligence for detecting early gastrointestinal cancer, predominantly during Endoscopy. | How can we use of artificial intelligence to further improve the detection and diagnosis of early gastrointestinal cancers? |
Epidemiology of Cancer Healthcare and Outcomes (ECHO), Behavioural Science and Health, Institute of Epidemiology and Health Care | Cancer healthcare epidemiology / Cancer data science / primary care records / electronic health records / diagnosis / detection. | How can we use population-based studies to examine the predictive value for cancer of different presenting features (e.g. symptoms, blood test results) and work to identify pathways and intervals to diagnosis and patients at higher risk of delayed / emergency diagnosis? |
Prof Juan Pedro Martinez-Barbera Developmental Biology and Cancer, UCL GOS Institute of Child Health | My lab's research focuses on understanding the role of senescent cells in cancer. We have developed tools and accumulated expertise to study senescent cells in the context of cancer and ageing. We also have identified and tested senolytics aiming to translate the basic research findings | Which cells become senescent during ageing and what are their function in prostate cancer? We have generated a new mouse model that allows to detect, isolate, trace and ablate senescent cells in ageing mice and in cancer. We have preliminary data indicating that senescent cells accumulate in the aged prostate and we aim to explore their role in prostate cancer. |
Dr Eleftheria (Laura) Panagiotaki Computational Cancer Microstructure Imaging Group, Centre for Medical Image Computing, Department of Computer Science | My research focuses on computational modelling of quantitative MRI and validation techniques, to establish new non-invasive biomarkers for cancer. An example is the VERDICT-MRI technique I developed for cancer imaging, the first non-invasive microstructure imaging method for cancer which is now in clinical trials. | Cancer increasingly affects people worldwide, with significant inter- and intra-tumoral heterogeneity complicating prognosis and treatment planning. How can we develop histology-informed AI computational MRI models of tumours for early diagnosis that will also predict which early-stage patients may or may not benefit from adjuvant treatments? |
Renal cell carcinoma (RCC) is one of the most common types of cancer in the UK with poor prognosis and increasing incidence worldwide. There is therefore an urgent need to develop better tools for the detection of early disease and identification of patients at higher risk of progression. | Natural killer cells play a critical role in anticancer defence. NK cell dysfunction/evasion by tumour cells correlates with renal cell carcinoma (RCC) progression and poor prognosis. How can we investigate the role of NK cells in RCC and their potential as a surveillance tool for early-stage RCC? | |
Institute for Liver & Digestive Health, Division of Medicine | Our translational and multidisciplinary group is interested in early detection of pancreatic cancer and cholangiocarcinoma using biomarkers, imaging, and multi-omics including proteomics and spatial biology | Can we refine and validate promising biomarkers signatures for the early detection of pancreatic and biliary tract cancer? |
Targeted Intervention, Division of Surgery and Interventional Science | My group develops novel ways to diagnose and treat cancer that combines biomarkers and imaging. In particular we identify and validate novel tissue and fluidic markers alongside pathology AI approaches and MRI data. | Can we utilise early changes in lymph node architecture to diagnose and treat pro-metastatic cancer before it spreads? |
Multiple Myeloma Lab, Department of Haematology, UCL Cancer Institute | Myeloma is the second most common haematological malignancy. Myeloma is invariably preceded by smouldering, an asymptomatic stage, which affects 0.5% of the population aged over forty. My laboratory focuses on understanding the transition from smouldering to active disease: identifying those that will progress and developing biomarkers to guide early decision-making. | A key unmet need in this setting is understanding the final stages of disease progression to identify likely progressors early. How can we use tumour and immune interactions, to understand and model the final steps of disease to prevent progression? |
Key dates:
Application deadline: Monday 4th November 2024
Interview date: week commencing 13th and 20th January 2025
Studentship start: October 2025