Research Associate/Fellow

Location: University Park

Applications are invited for an experienced bioinformatician to join the Deep Seq facility, where you will take responsibility for the analysis and interpretation of Next Generation Sequencing (NGS) datasets generated on a range of cutting-edge platforms.

The successful candidate will provide expert analytical support and advice to facility users, helping them to extract maximum biological insight from their data. This will require effective communication with researchers from diverse backgrounds and the ability to translate between biological questions and computational analysis.

You will be expected to plan and conduct your own analyses using available tools, to adapt existing methodologies and scripts, and to design new pipelines and workflows that deliver accurate, reproducible, and timely results. You will also be responsible for preparing analysis reports, user summaries, and contributing to publications.

The facility specialises in running Oxford Nanopore Technologies (ONT) MinION, GridION, and PromethION instruments—experience in the analysis of ONT data is therefore a significant advantage although training can be provided. Deep Seq currently operates short read platforms from Element and Illumina, single cells technologies including 10x Genomics platforms and otthers. The facility maintains several dedicated servers and HPC resources for data processing, and the post holder will take a leading role in their management and optimisation.

This position offers an excellent opportunity to further develop bioinformatics expertise in a dynamic, multidisciplinary environment, with scope to design and implement novel computational tools and expand your analytical portfolio.

Candidates should hold a PhD (or be near completion), an MSc in Bioinformatics, or have equivalent professional experience in bioinformatics, computational biology, or a related field. Proficiency with Linux operating systems is essential, as is the ability to analyse and interpret large datasets and apply critical evaluation to current methodologies.

Applicants must demonstrate strong programming skills in at least one scripting or programming language (e.g. Python, R, Perl, Nextflow, C++, or Java) and experience in areas such as database management, sequence alignment and assembly, variant and methylation calling, RNA-Seq analysis, and integration of public datasets. Familiarity with workflow management systems (e.g. Snakemake, Nextflow) and experience using HPC environments would be advantageous.

This is a full time permanent post (36.25 hours per week). Flexible working arrangements and job share arrangements may be considered.

Informal enquiries may be addressed to Matthew Loose (matthew.loose@nottingham.ac.uk).  Please note that applications sent directly to this e-mail address will not be accepted.

Further details:

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