Research Fellow or Senior Research Fellow - Bioinformatics and Statistical Modelling

About the role

The post-holder will be expected to work closely with “wet” lab scientists, clinicians and other computational biologists. Applicants from computational or biological backgrounds will be considered, but proficiency in R or Python and Bash scripting will be prioritised. A familiarity with cancer genomics and machine learning algorithms is highly desirable.

Salary offered will either be on UCL Grade 7 (£42, - £50,) or Grade 8 (£51, - £60,) per annum including London Allowance dependent on qualifications and experience. 

Appointment at Grade 7 is dependent upon having been awarded a PhD; if this is not the case, initial appointment will be at research assistant Grade 6B (salary £37, - £39, per annum including London Allowance) with payment at Grade 7 being backdated to the date of final submission of the PhD thesis.

Appointment at Grade 8 is at the discretion of the hiring manager, , Dr Nischalan Pillay. In order to be considered for Grade 8, the candidate should have gained an independent research reputation with evidence of national or international recognition of achievements in their area of research. They should show evidence of original, completed and published research on which they are first or senior author, as well as a suitable publication record, and evidence of knowledge transfer/exchange activities. In addition, they need to have experience in leading small teams of researchers and giving talks at international workshops and conferences.

Informal enquiries regarding the vacancy can be made by email to Dr Nischalan Pillay at

Please see the attached job description and person specification for full details.

All applications must include a supporting statement telling us, using examples, how you meet the essential criteria listed in the job description. Applications without a supporting statement will be rejected.

For enquiries regarding the application process please contact Cancer Institute HR Office .

About you

Candidates should hold or about to be awarded a PhD in either computational biology, bioinformatics, and/or statistical genetics with relevant experience in genomics, computational modelling work and bioinformatics and must have a proven track record of research achievements. Candidates should ideally have experience in analysing cancer genomic data and excellent programming skills in R or Python. Previous experience in cancer genomics, statistical analysis and machine learning would be an advantage. Candidates will need to have the initiative to work independently and as part of a team. Due to the highly interdisciplinary nature of this project, effective communication skills are key.

Applicants must have experience in presenting complex scientific concepts and content both in writing and verbally. They will show a strong commitment to the Pillay laboratory mission and embody its values through excellent collaborative interpersonal skills with an ability to work co-operatively in a multidisciplinary setting.

Excellent communication skills and the ability to work well in a multidisciplinary team are essential. The post-holder will be expected to have the ability to assist other members of the Pillay laboratory, supervise BSc, MSc and/or PhD students, collaborate with external research groups, as well as contributing to the organisation and smooth operation of the Pillay laboratory. 

What we offer

As 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

The advert will close on 1st October at 23:59 GMT, however we may close applications early if we receive a high volume of applications. Early application submission is recommended.

Closing an advert early:

In the event we get a high number of applications, we may close the advert early before the published closing date. As a minimum we will keep all adverts open for 2 weeks.