The main objective of this post-doctoral research associate post is to identify and investigate molecular and imaging patterns favourable for immunotherapy in non-small cell lung cancer. The candidate will work with molecular readouts (spatial transcriptomics and mutational panel data) from lung cancer tissue, liquid biopsy, clinical and multi-modal medical imaging data.

The post-holder will be a core scientist on the project, which is led by Dr Mitch Chen, MRC Clinician Scientist and Consultant Radiologist

You will conduct laboratory research to gather preliminary data and undertake comprehensive enrichment analysis of multi-omics data. You will also undertake works on developing deep learning models for bridging imaging and molecular data to advance lung cancer precision oncology.

The candidate should have a PhD and research experience in machine learning, bioinformatics and/or cancer research. Additional experience in software product development is desirable but not compulsory. The candidate is expected to have a good track record of self-driven research work (independent or under indirect supervision), excellent verbal and written communication skill, and ideally experience working in a healthcare research setting.

You will be part of a multi-disciplinary team of senior academics, clinical and non-clinical researchers, PhD students and technicians. You will have the opportunity to participate in regular lab meetings, departmental research meetings, and supervise research students.

The post-holder will have the opportunity to gain inter-disciplinary research experience in cancer multi-omics, bioinformatics and artificial intelligence, present at national and international conferences, and prepare manuscripts as first or joint author for submission to leading cancer, radiology and machine learning journals.