We are seeking a graduate with experience in computational biology, statistics, computer science or molecular/cellular biology with a first class honours degree or equivalent to join a leading multidisciplinary research group focusing on the integration and analysis of large-scale (epi)genetic and (epi)genomic data as well as on focussed target gene approach studies to understand the role of dysregulated epigenetic mechanisms in initiation and progression of brain tumours (Vinel et al. Nat. Commun. 2021, Freire-Benéitez et al NAR Cancer 2021, Dumas et al EMBO J 2020 and Ricci, Millner et al Oncogene 2020).
We have developed a novel experimental pipeline to characterise molecular pathways and genes specifically deregulated in GBM in a patient-specific fashion (SYNGN) and have identified novel drugs effective against these tumours at pre-clinical level (Vinel et al Nat. Commun 2021). Evolution of resistance to drug treatment in cancer is a common cause of tumour progression. The successful candidate will use genetic labelling and mathematical modelling (Williams et al. Nat. Genet 2018, Gabutt et al Nature Biotech 2022) to understand the frequency of naturally occurring drug-resistant clones, and the dynamics of their evolutionary emergence during the treatment with the novel compounds we have identified. This approach will inform the subsequent design of the further pre-clinical validation in vivo.
The post is based in the Blizard Institute (wet lab component, under the supervision of Prof Marino) and Barts Cancer Institute (computational component, under the supervision of Prof Graham).
All applicants should have a strong motivation for pursuing an ambitious research agenda in an international and competitive research environment.
Start date is April or September 2022.
Please use this link to apply: https://mysis.qmul.ac.uk/urd/sits.urd/run/siw_ipp_lgn.login?process=siw_ipp_app&code1=RFQM-W1XF-05&code2=0013