Research Fellow

Job title:

Research Fellow

Company

University College London

Job description

About usThe Hall and Enver groups share a common interest in the study of cancer evolution. This cross-disciplinary project brings together the Hall group’s expertise in the development of computational biology methods and their application to understanding the mechanisms shaping carcinogenesis and the Enver lab’s long-standing interest in the application of the principals of stem cell biology and cell fate regulation to the study of cancer.Prof Hall is situated in the department of Medical Physics & Biomedical Engineering, a global leader in cross-disciplinary medical sciences that fosters collaborations between clinicians and scientists. The laboratory of Prof Enver is in the Cancer Institute which fosters links between basic cancer researchers across Biomedicine, and with the clinical activities of our partner Hospitals.About the roleWe are looking for a talented Research Fellow to join this cross-disciplinary project with co-leads Professors Ben Hall and Tariq Enver.This project will use transcriptomic data from BCP-ALL patients at diagnosis and relapse to develop patient-cohort models to explain how mutations and epigenetic changes combine to determine cellular fate, through a data-driven executable modelling approach. The resulting models will allow in silico perturbations to be performed, identifying key nodes and candidates for therapeutic targeting. Promising therapeutic candidates will be tested using established experimental models in the Enver lab.The post if funded until June 2026 in the first instance.Appointment at Grade 7 is dependent upon having been awarded a PhD; if this is not the case, initial appointment will be at Grade 6B (salary £37,332 – £39,980 per annum including London Allowance) as Research Assistant with payment at Grade 7 being backdated to the date of final submission of the PhD Thesis.About youThe successful candidate must have (or be studying for) a PhD in computational biology or a related discipline. Experience in computational modelling (systems biology, though related transferable fields will be considered), as is experience in handling large scale public datasets.The candidate will have the ability to work independently, set priorities and meet deadlines and demonstrable programming skills including fluency in one or more of: bash/R/Python. Ability to collaborate, and to work as part of a team encompassing computational and experimental biologists is also essential.Experience in writing scientific manuscripts and of teaching/supervision is not essential but would be desirable.What we offerAs well as the exciting opportunities this role presents we also offer some great benefits some of which are below:

• 41 Days holiday (including 27 days annual leave 8 bank holiday and 6 closure days)
• Defined benefit career average revalued earnings pension scheme (CARE)
• Cycle to work scheme and season ticket loan
• On-Site nursery
• On-site gym
• Enhanced maternity, paternity and adoption pay
• Employee assistance programme: Staff Support Service
• Discounted medical insurance

Our commitment to Equality, Diversity and InclusionAs London’s Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world’s talent. We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong.We therefore particularly encourage applications from candidates who are likely to be underrepresented in UCL’s workforce.These include people from Black, Asian and ethnic minority backgrounds; disabled people; LGBTQI+ people; and for our Grade 9 and 10 roles, women.You can read more about our commitment to Equality, Diversity and Inclusion here :Available documents

Expected salary

£37332 – 39980 per year

Location

North West London

Job date

Thu, 01 Aug 2024 05:02:01 GMT

To help us track our recruitment effort, please indicate in your email/cover letter where (globalvacancies.org) you saw this job posting.