Postdoctoral Research Scientist

Applications are invited for a Postdoctoral Research Scientist to join the Research Faculty Department at the Earlham Institute, based in Norwich, UK.

Background:

In humans, over 90% of the variants associated with traits are found within noncoding regions of the genomes, either within genes' introns, untranslated regions, promoters, or within intergenic regulatory regions such as enhancers. 

Identifying those functional noncoding sequences and being able to predict the impact of variation within those regions has significant implications. As such, depending on the genetic disorder, between 30% and 70% of the patients do not receive a genetic diagnosis as the likely causative variants fall outside coding sequences.

The recently funded Horizon NextGen consortium encompassing 21 organisations across Europe aiming at developing federated approaches to enable the integration of multimodal and multiomic resources for applications in the areas of cardiovascular medicine. 

As part of this highly collaborative project bringing together computer scientists, data scientists, bioinformaticians, clinicians across academia and industry, we are seeking an enthusiastic and ambitious postdoctoral research scientist to undertake computational analysis of the functional implications of variation within noncoding functional sequences in relation to cardiovascular disorders.

As part of the EU Horizon / Innovate UK funded project “Next Generation Tools for Genome-Centric Multimodal Data Integration in Personalised Cardiovascular Medicine”, the role will engage with primary research. 

The post holder will work closely with external partners and members of the EU consortium, and will focus on developing machine learning applications to investigate the implications of genetic variation within noncoding functional elements in relation to cardiovascular disorders.

The role:

The post holder will lead on the development and testing to applications to identify noncoding functional elements based on integration of multi-omic data (genome, transcriptome, epigenome) and integrate this novel information in the development of tissue / condition specific regulatory network, with the aim of prioritising variants occurring within those regions based on their predicted impact. They will also lead on the analysis, preparation, and submission of the associated manuscripts.

The successful candidate will develop computational pipelines centered on machine learning applications such as convolutional neural network to reproducibly handle multi-omic data (genome, transcriptome, epigenome) to enable functional sequence annotation, network reconstruction, and the interpretation of the implication of genetic variation within those disorders.

The post holder will have access to cutting-edge high performance computing facilities and expertise. They will join an active community of experimental and computational biologists working on a wide range of genomics analyses. They will also have the opportunity to contribute to other projects at EI.

The ideal candidate:

The successful applicant will have a PhD in bioinformatics, computational genomics or a related subject. 

They will have significant experience working with genomic/epigenomic/transcriptomic data, and experience with machine learning applications in genomics investigations. The candidate should have a demonstrable working knowledge of programming languages such as Python, Perl, or R.

Additional information:

Salary on appointment will be within the range £35,300 to £43,750 per annum depending on qualifications and experience.  This is a full-time post until 31 December 2027, with a possibility of a 6-month extension.

This role meets the criteria for a visa application, and we encourage all qualified candidates to apply.  Please contact the Human Resources Team if you have any questions regarding your application or visa options.

As a Disability Confident employer, we guarantee to offer an interview to all disabled applicants who meet the essential criteria for this vacancy.

The closing date for applications will be 11 June 2024.