The MRC Cancer Unit (MRC CU) is a University Department situated on the Cambridge Biomedical Campus. It provides an outstanding environment for cancer research, supporting some 10 research groups and ~100 bench scientists. The successful candidate will be joining an exciting research group headed by Dr Shamith Samarajiwa. 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 can be found at http://www.mrc-cu.cam.ac.uk/samarajiwa.html
The research focus of the project is to develop and apply artificial intelligence methods and technologies within a research programme of integrative cancer systems biomedicine. The role involves the application and development of AI methods to decipher, understand and make inferences from large cancer and functional genomics datasets. The candidate will have a PhD (or equivalent) in artificial intelligence or a related discipline (machine learning, deep learning) and 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 bio-medical problems would be useful.
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, SkLearn and other DL/ML libraries is required. Experience in a Linux/Unix environment, with excellent programming skills in Python and R is required whilst knowledge of C/C++, C# would be advantageous. The ability to deal with large and heterogeneous data sets 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 CPU/GPU university HPC 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 1 April 2018 until 31 March 2020.
For candidates with a PhD the salary will be on the scale £31,604 - £38,833 p.a. 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 £28,936 p.a. (Grade 5) and, if applicable, advancing to Grade 7 Research Associate level following the conferment of your PhD.
For queries regarding this post please contact firstname.lastname@example.org
Once an offer of employment has been accepted, the successful candidate will be required to undergo a security check.
To apply online for this vacancy, please click on the 'Apply' button below. 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 and CV including a list of publications 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 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 Sunday 11th February 2018 and interviews will likely be held on w/c 26th February 2018.
Please quote reference SK14533 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.
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