UCL Division of Biosciences


SysMIC - Online training in data analysis, programming and modelling for Bioscientists

Over 3000 bioscientists from more than 100 institutes have trained with SysMIC, completing over 150,000 hours of learning.

Our aim is to develop the skills our participants will need to effectively support interdisciplinary research and collaboration. These include analysing data, developing algorithms, creating system models and advanced mathematical techniques.

Participants will become confident in using the three most widely used research computing platforms so that they are able to manage challenging data sets and access new ways of working.

Interdisciplinary research in biosciences is becoming increasingly more important. Biology is also becoming a more quantitative science. However, many biologists do not have sufficient maths and computing experience for this move. Ensure that you are prepared for the challenges of 21st-century biosciences by improving your understanding of data analysis, modelling and programming.      

Apply now

What do Students have to Say About SysMIC?

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An Overview of the SysMIC Programme

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UCL Biosciences

 UCL is ranked 8th in the 2020 QS World University Rankings, Biological Sciences was ranked 10th in the world* and Human Biological Sciences was ranked 3rd in the world and 1st in Europe* (*ShanghaiRanking's Global Ranking of Academic Subjects 2018)

With origins tracing back to 1826, UCL has been home to some of the greatest figures of evolutionary biology from Robert Grant to John Maynard Smith to our current world-leading scientists. 

darwin blue plaque on biosciences building UCL Gower Street london

Designed by Bioscience Researchers for Bioscience Researchers

colourful beakers in lab


SysMIC consists of 5 hours of study a week over 6 months. The SysMIC online data analysis programme was specifically designed to be flexible and to fit around research commitments.

Course material is always available and our schedule of study can be adapted to suit your needs.

Our Modules

Module One: Introduction in Quantitative Skills for Bioscience

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  • Introduction to MATLAB programming
  • Working with networks
  • Modelling systems
  • Statistical analysis using R
  • Coding in Python
  • Building a toolbox for sequence analysis


Module Two: Advanced Quantitative Skills for Bioscience

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  • Discrete systems
  • Principal Component Analysis (PCA)
  • Bistable systems
  • Spatio-temporal systems
  • Stochastic systems
  • Parameter fitting (classical & Bayesian)