Research Associate - Computational Biologist/Bioinformatician (Fixed Term)
Closing date: 30th January 2020
Fixed-term: The funds for this post are available for 2 years in the first instance.
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 modification of DNA and RNA. This position provides opportunities to collaborate with experimental scientists across the chemistry-biology interface from experimental design to the analysis of novel types of data. The post-holder will work as a bioinformatics analyst contributing to several project domains 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
- Identification and mapping of 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)
Key functions of the role include:
- Using existing pipelines or implementing new ones to play a leading role in experimental design, sample size estimation, data QC, visualization, analysis, interpretation and documentation of genome-wide datasets.
- Performing and developing ad hoc analyses with customised and novel algorithms on experimental datasets obtained from novel ChIP-Seq, RNA-Seq, modified base and other genome sequencing methodologies. This encompasses, for example, expected outcome simulation, signal normalization, data mining, enrichment detection and prediction of secondary structures.
- Managing research collaborations and 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.
- 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).
- Knowledge of biological data banks (e.g., NCBI, EMBL-EBI, Ensembl, KEGG, ENCODE).
- Ability to share own code (e.g. GitHub).
Applicants should have a strong foundation in statistical methods and computational science with a PhD in a computational discipline such as computer science, quantitative biology, bioinformatics or computational biology/chemistry. Previous experience in analysing genomic datasets, especially NGS data, is highly desirable. For academic candidates a consistent record of strong scientific publications is essential. We also welcome candidates with equivalent relevant industrial experience. The position requires strong communication and teamwork skills and involves regular interactions with our research scientists and computational researchers. The successful candidate will be highly organized, with good time management and the ability to support multiple concurrent projects. Experience in project management would also be welcomed.
Only candidates who apply through the University online recruitment system will be considered. Please ensure that you upload your Curriculum Vitae (CV) and a covering letter in the upload section of the online application. If you upload any additional documents that have not been requested, we will not be able to consider these as part of your application. Apply online
For queries relating to your application or the application process, please contact Jo Lockhart, PA to Professor Sir Shankar Balasubramanian (BalasubramanianRecruitment@ch.cam.ac.uk).
Please quote reference SW21804 on your application and in any correspondence about this vacancy.