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Research Associate
A Research Associte position is available to join an innovative data-science research group headed by Dr Shamith Samarajiwa at the MRC Cancer Unit. The research focus of the group is to integratively uncover the fundamental rules underlying gene, genome and epigenome regulation during both normal cellular processes and their perturbation during pathological conditions such as cancer.
More information about the MRC Cancer unit is at https://www.mrc-cu.cam.ac.uk/ and the Samarajiwa lab can be found at https://samarajiwa-lab.org
The research focus of this project is to develop and apply artificial intelligence (AI) methods and technologies to understand gene and epi(genomic) regulatory mechanisms involved in cancer with a perticular focus on immune and inflammatory processes. The project will utilise genomic datasets relating to gene expression (RNA-seq), gene and epigenome regulation (ChIP-seq, ATAC-seq, Drip-seq, Ribo-seq, Hi-C etc), together with cancer genomic datasets such as WGS to identify CNV (mutations), CNAs (genetic abberations) and mutational signatures. The Samarajiwa lab has considerable expertise in developing integrative computational methods and applying data science and computational biology to understand and mine genomic datasets. The data-sets used are generated by our collaborators or are from large public data-generation efforts.
The role involves the application and development of Data Science and AI methods to decipher, understand and make inferences from the above cancer and functional genomics datasets. The candidate will ideally have a PhD in artificial intelligence (machine learning, deep learning) or a related discipline (Computational Biology, Computer Science, Engineering or Mathematics with experince in deep learning and machine learning).
A good peer reviewed publication record or relevant innovation experience in industry together with demonstrable experience in implementing or applying machine learning algorithms or models is expected. Experience in deep learning and use of Tensorflow, Keras, scikit-learn and other DL/ML libraries is required. Experience in a Linux/Unix environment, with excellent programming skills in Python is required whilst a knowledge of R would be advantageous. The condidate should have a good understanding of neural network architectures, have necessary statistical knowledge, programming and computer science skills required for applied AI research. While knowledge of biology is not required an enthusiasm for the application of AI methods to solve biomedical problems would be useful.
The ability to deal with large and heterogeneous datasets and an ability to carry out reproducible computational research is also expected. Access to an internal CPU compute cluster, an internal GPU server and access to the large Cambridge University high performance computing cluster will be provided. The applicant is expected to work in a multidisciplinary team consisting of genomicists, clinicians, computational biologists, mathematicians and computer scientists and training in computational biology, genomics and cancer biology required for the project will be provided.
This fixed-term position is funded by Isaac Newton Trust/Wellcome Trust ISSF and University of Cambridge Joint Research Grants Scheme and is available from immediately until 31 March 2020.
For candidates with a PhD the salary will be on the scale £31,604 - £38,833pa depending on relevant postdoctoral experience. Candidates without a PhD or due to complete their PhD within 6 months of their start date will be appointed at the Research Assistant level with a salary of £28,936pa (Grade 5) and, if applicable, advancing to Grade 7 Research Associate level following the conferment of your PhD. Applicants should include a letter outlining suitability for the role, a CV including a list of publications and the contact details for 3 academic referees. Any offer of employment is subject to security screening. To apply online for this vacancy please visit http://www.jobs.cam.ac.uk/job/16356/ . This will route you to the University's Web Recruitment System, where you will need to register an account (if you have not already) and log in before completing the online application form. Please ensure that you upload a covering letter outlining your suitability for the role, CV and the contact details of two employment referees in the Upload section of the online application. 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 quote reference SK41533 on your application and in any correspondence about this vacancy. Applications received after the deadline may be considered at the discretion of the assessing panel.
For queries regarding this post please contact admin@mrc-cu.cam.ac.uk
Closing date for applications is 8 April 2018
Interviews will be held w/c 16 April 2018