Jason Ran

The CDT at UCL, with its focus on data science and physics, was a natural progression in my academic journey.

Project title: Bayesian Methods for Planet Formation

Research Group: Astrophysics

Supervisor(s): Dr Mihkel Kama

Introduction: 

My academic journey prior to UCL was characterised by a diverse range of projects spanning various fields, highlighting the interdisciplinary nature of my interests. This was especially evident during my MSci in Physics at Imperial College London, where I delved into space weather simulations and machine learning. Joining the CDT at UCL, with its emphasis on data science and physics, felt like a natural continuation of my academic trajectory.

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Project description:  

Cutting-edge machine learning and statistical methods have revolutionised exoplanet research. Through my PhD, I will explore applications of these methods to the closely related field of planet formation, especially regarding the resulting exoplanet populations and origins of chemical diversity.

First year group project: Biologically Informed Neural Networks for Radiosensitivity Prediction - UCL Department of Medical Physics and Biomedical Engineering

Placement: 

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