Fixed-term: The funds for this post are available for 2 years in the first instance.
This is an exciting opportunity for a highly motivated computational researcher to join Professor Sir Shankar Balasubramanian’s pioneering research programme playing 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 two other bioinformaticians, applying their expertise across the group. The role will focus on innovative technology and translational research. We welcome candidates with industrial experience. They will have opportunity to carry independent research in close collaboration with experimental scientists and take advantage of cutting edge HPC AMD infrastructure.
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 (e.g. 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 (e.g. 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 and ELIXIR) and bioinformatic tools.
– Algorithm development, data mining and statistical analysis of large datasets (e.g. Bayesian statistics, Markov models, simulation models or machine learning).
– Experience collaborating with experimental chemists or biologists, and managing several concurrent projects with changing priorities.
Applicants should have a strong foundation in statistical methods and computational science with a PhD in a discipline such as bioinformatics, computational biology/chemistry, computer science or quantitative biology. Previous experience in analysing genomic (especially high-throughput sequencing data) and other type of biological datasets is highly desirable. Candidates with structural bioinformatics background are strongly encouraged. For academic candidates a consistent record of strong publications is essential. The position requires strong communication and teamwork skills and involves regular interactions with researchers across the group’s laboratories at CRUK Cambridge Institute and Yusuf Hamied Department of Chemistry. The successful candidate will be highly organized with good time management skills. Experience in project management is welcomed.
To apply online for this vacancy and to view further information about the role, please click on the apply button above.
See www.balasubramanian.co.uk/ for further information.
Please upload a 2-page Curriculum Vitae (CV), a covering letter and publications list in the Upload section of the online application.
For any queries, please contact Jo Lockhart, Science Administrator, email: BalasubramanianRecruitment@ch.cam.ac.uk.
The Department holds an Athena SWAN silver award for women in science, technology, engineering, mathematics and medicine.
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.
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