Yusuf Hamied Department of Chemistry

This is an exciting new opportunity for a highly motivated computational researcher to join Professor Sir Shankar Balasubramanian's pioneering research programme to play a key role in advancing the understanding of sequence, structure and chemical modifications in DNA and RNA. Using their expert knowledge of programming languages, statistical/machine learning methods, bioinformatics tools and resources, the ideal candidate will use and develop computational approaches to transform raw sequencing data into biologically meaningful information. The successful candidate will have strong problem analysis/solving skills and be able to work collaboratively within a multidisciplinary team working at the interface between chemistry, biology and bioinformatics. This is a vital post and the applicant will join a small team, with two other bioinformaticians, applying their expertise across the group. The role will be focussed on innovative technology and on translational research and we would welcome candidates with industrial experience.

Key functions of the role include:

• Playing a leading role in experimental design.
• Performing, customising and/or developing computational analyses/algorithms for raw data from sequencing-based assays such as ChIP-seq and RNA-seq and other data types (e.g. proteomics).
• Pre-processing of raw datasets and high-level analysis and visualisation to enable interpretation and deduce new biological insights.
• Managing research collaborations with experimental scientists and developing independent projects.

Skills required include:

• Programming/scripting skills in languages such as R or Matlab, Python or Perl, C/C++, Ruby or Java.
• Working knowledge of Linux/Unix, with experience in data processing in an HPC cluster environment and basic understanding of computer systems administration.
• Knowledge of biological data resources (e.g., NCBI, EMBL-EBI, KEGG, ENCODE and ELIXIR) and bioinformatic tools.
• Algorithm development, data mining and statistical analysis of large datasets (such as Bayesian statistics, Markov models, simulation models or machine learning).
• Experience collaborating with experimental scientists e.g., chemists or biologists, and managing several concurrent projects with changing priorities

https://www.jobs.cam.ac.uk/job/37709/