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Environment
Imperial College London is consistently rated as one of the World’s leading universities (https://www.topuniversities.com/university-rankings/world-university-rankings/2022). Imperial’s Department of Bioengineering has a strong international profile and currently hosts about 230 PhD students, thus providing a supportive and stimulating environment to carry out a PhD. It was declared UK’s top department of bioengineering for research in the latest Research Excellence Framework. The department has a strong computational and theoretical modelling theme, and participates in Imperial networks such as the AI Network, the Centre for Drug Discovery Science and the CRUK Convergence Science Centre (https://www.convergencesciencecentre.ac.uk/) between Imperial (https://www.imperial.ac.uk/) and ICR (https://www.icr.ac.uk/).
Project
This project will investigate the application of artificial intelligence (AI) methods to precision oncology (PO). PO is a form of medicine that uses personal information to prevent, diagnose and treat cancers. Here we focus on the PO topic of how to predict which cancer patients will respond to a given drug treatment from the molecular profiles of their tumours. There are major methodological challenges limiting the potential of such AI models. Some are specific to this problem (e.g. how well a rare cancer type can be predicted using data from other types?). Other challenges are also found in other supervised learning problems (e.g. how to improve supervised learning when training with high-dimensional data?). This PhD project aims at making progress towards overcoming these challenges using both synthetic and real datasets.
Selection criteria - Essential
University degree/s awarded in an area directly relevant to the project.
Courses in the application of machine learning algorithms to scientific problems.
Excellent grades in first and/or master degrees, especially in their research projects, with a major focus on computational analysis of data.
Skilled in the implementation of Python or R scripts for scientific data analysis.
English language (https://www.imperial.ac.uk/study/pg/apply/requirements/english/).
Selection criteria - Desirable
Research projects in the application of supervised learning to solve real-world problems in the context of biomedical research, especially precision medicine.
Some understanding of tumour profiling (omics), cancer biology and clinical oncology.
Ideally, trained on handling, integrating, processing and analysing molecular profiling data (e.g. DNA-seq, RNA-seq, miRNA-seq and/or DNA methylation microarrays).
Exposure to machine learning platforms (e.g. Scikit-Learn, Caret), and/or pharmaco-omic databases (e.g. GDC, GDSC).
Exposure to the application of machine learning algorithms to low-sample problems.
·Familiarity with clinical cancer pharmaco-omics databases (e.g. GDC).
How to apply
Candidates must send an email with their CV, grades for each held university degree and a covering letter (maximum two pages) to [Email Address Removed] with subject line “PhD in AI for PO”. This letter must explain how they meet the essential selection criteria, which desirable selection criteria are also met and how this position would fit in their future career plans. This email must also state the names and emails of two scientists involved in assessing their academic performance, who are willing to provide a reference. Please also mention in the letter where did you see this position
Research output data provided by the Research Excellence Framework (REF)
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