We seek a highly motivated computational researcher for a key role within Professor Sir Shankar Balasubramanian's pioneering research programme at the Cancer Research UK Cambridge Institute (CI). Our research focuses on the chemical biology of the genome and epigenome (https://www.balasubramanian.co.uk/publications). Our lab invents and applies new computational methods for the analysis of sequence, structure and chemical modifications in DNA and RNA. This position provides opportunities to develop computational tools at the interface between chemistry, biology and bioinformatics from experimental design to the analysis of novel types of data in collaboration with talented experimental scientists. The post-holder will work as a bioinformatics research scientist contributing to several research areas such as:
- Elucidating the fundamental role of non-canonical nucleic acid structures, such as G-quadruplexes, in the genome and transcriptome (e.g. Chambers et al., Nature Biotechnology 2015, DOI: 10.1038/nbt.3295; Hänsel-Hertsch et al., Nature Genetics 2016, DOI: 10.1038/ng.3662; Marsico et al., Nucleic Acids Research 2019, DOI: 10.1093/nar/gkz179; Zyner et al., eLife 2019, DOI: 10.7554/eLife.46793).
- Identification and mapping of chemically modified bases, such as cytosine and thymidine modifications, and understanding their function in the genome and epigenome (e.g. Booth et al., Science 2012, DOI: 10.1126/science.1220671; Bachman et al., Nature Chemical Biology 2015, DOI: 10.1038/nchembio.1848; Kawasaki et al., Genome Biology 2017, DOI: 10.1186/s13059-017-1150-1; Hofer et al., J. Am. Chem. Soc. 2019, DOI: 10.1021/jacs.9b01915; Liu et al., Nature Chemistry 2019, DOI: 10.1038/s41557-019-0279-9)
Key functions of the role include:
- Playing a leading role in experimental design, data analysis, visualization and interpretation of genome-wide omics datasets by implementing new computational tools or using existing ones.
- Performing and developing computational analyses with customised and novel algorithms on experimental datasets obtained from novel ChIP-Seq, RNA-Seq, modified base mapping and other genome sequencing, transcriptomics and proteomics methodologies. This encompasses, for example, expected outcome simulation, signal normalization, data mining, enrichment detection and prediction of secondary structures.
- Managing research collaborations with experimental scientists and developing independent projects.
Skills required include:
- Excellent programming/scripting skills in languages such as R or Matlab, Python or Perl, C/C++, Ruby or Java.
- A good working knowledge of Linux/Unix, with experience in data processing in an HPC cluster environment and basic understanding of computer systems administration.
- Algorithm development, data mining and statistical analysis of large datasets.
- Experience in statistical modelling and mathematical tools (e.g. Bayesian statistics, Markov models, simulation models or machine learning).
- Knowledge of biological data resources (e.g., NCBI, EMBL-EBI, KEGG, ENCODE and ELIXIR).
- Experience collaborating with experimental scientists e.g. chemists or biologists, and managing several concurrent projects with changing priorities
- Ability to version control and share research code (e.g. git/GitHub).
Applicants should have a strong foundation in statistical methods and computational science with a PhD in a computational discipline such as bioinformatics, computational biology/chemistry, computer science or quantitative biology. Previous experience in analysing genomic datasets, especially high-throughput sequencing data, is highly desirable. For academic candidates a consistent record of strong scientific publications is essential. We also welcome candidates with equivalent industrial experience. The position requires strong communication and teamwork skills and involves regular interactions with research scientists and computational researchers within the chemical biology laboratories. The successful candidate will be highly organized, with good time management and the ability to develop multiple projects in parallel. Experience in project management would also be welcomed.
Please quote reference SW23854 on your application and in any correspondence about this vacancy.
For more information, please email: Jo Lockhart, Science Administrator, Balasubramanian Group (BalasubramanianRecruitment@ch.cam.ac.uk)