Research Associate (Fixed Term)
We are looking for a motivated and talented postdoctoral researcher in the areas of Statistics and Machine Learning to join the research group led by Dr Oscar Rueda at the MRC Biostatistics Unit, focused on developing statistical models for prognosis and monitoring of cancer patients. It sits within the Unit's Precision Medicine theme, sharing a common vision to better characterize clinical and biological heterogeneity in order to improve understanding, prognosis, prediction, tailoring of treatment and healthcare decisions.
The successful candidate will work on projects related to the development of novel methodology to identify latent structures in multimodal molecular datasets. There is considerable flexibility on the modelling approach depending on the background or research interests, so the candidate may focus on Bayesian Statistical methods, Variational Autoencoders or related Machine Learning techniques. There will be a strong component on biological interpretation of the models, as well as enhancing the translational potential of the results.
The research associate will work in collaboration with other members of the group as well as other researchers from other groups in the Unit and experts in other fields from other departments, therefore a collaborative approach to research and good communication skills are essential.
The successful candidate should have recently finished or be in the latest stage of a PhD in a strongly quantitative discipline, such as (bio)statistics, Computational Biology or statistical machine learning, with experience in the analysis of high-throughput cancer molecular data, such as RNA-SEQ, methylation or DNA-SEQ (mutation calling and copy number data). Experience in the analysis of drug screening data and CRISPR/Cas9 would also be very relevant. Knowledge of the relevant Statistical and Machine Learning methodology, such as Bayesian Latent Modelling or Variational Autoencoders is also required, as well as good R/Python good programming skills. Support for career development will be provided, with a range of courses and on-the-job training.
This is a fixed-term position and the funds for this post are available for 3 years in the first instance.
For an informal discussion about this post, please contact Dr Oscar Rueda at: Oscar.rueda@mrc-bsu.cam.ac.uk.
The MRC Biostatistics Unit is one of Europe's leading biostatistics research institutions. Our focus is to deliver new analytical and computational strategies based on sound statistical principles for the challenging tasks facing biomedicine and public health.
The Unit is situated on the Cambridge Biomedical Campus, one of the world's most vibrant centres of biomedical research, which includes the University of Cambridge's Clinical School, two major hospitals, the MRC Laboratory of Molecular Biology, and the world headquarters of Astra Zeneca.
The Unit is actively seeking to increase diversity among its staff, including promoting an equitable representation of men and women. The Unit therefore especially encourages applications from women, from minority ethnic groups and from those with non-standard career paths. Appointment will be made on merit.
The Biostatistics Unit is committed to supporting hybrid working for all staff, but we do expect that staff will work from the office on a regular basis to help integration and to build our fantastic scientific community. Working entirely from the office is possible.
We welcome applications from those wishing to work part-time.
Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.
Please ensure that you upload a covering letter and a CV in the Upload section of the online application. The covering letter should outline how you match the criteria for the post and why you are applying for this role. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.
Please include details of your referees, including email address and phone number, one of which must be your most recent line manager.
The closing date for applications is: 10th November 2024
The interview date for the role is: To be confirmed
Please quote reference SL43698 on your application and in any correspondence about this vacancy.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.