University of Liverpool - Computational Biology Data Scientist (1FTE, £39,355 - £45,413 pa )

University of Liverpool - Computational Biology Data Scientist (1FTE, £39,355 - £45,413 pa )

Job Title: Computational Biology Data Scientist (1FTE, £39,355 - £45,413 pa )

Category: Technical roles

Closing Date: 08/04/2025

We are seeking a data scientist (PDRA-equivalent) with experience in bioinformatics, computational biology or similar discipline to contribute to scientific projects using omics and multi-omics analysis to support two newly launched Cystic Fibrosis Innovation Hubs: Pulse-CF (University of Manchester) and CF-TrailFinder (University of Liverpool). The post is initially funded for 4 years, but there may be potential to extend the term. Additionally, there could be an opportunity for the post to transfer into the Research Technical Professional Career Pathway at Liverpool, to embed within a full career progression at the Computational Biology Facility. This is an exciting opportunity to contribute to these very impactful hubs, engaging with clinicians and wet lab scientists to deliver on translational science, by applying data science skills to improve our understanding of cystic fibrosis exacerbations and their treatment.

Computational Biology Facility (CBF)

The CBF is a shared research facility within Liverpool Shared Research Facilities (LIV-SRF). LIV-SRF helps to ensure that staff have access to the world-class equipment and expertise to pursue outstanding science. The CBF aims to develop and support data-driven biological and clinical research by nurturing a team of specialists that work on forming new collaborations and delivering on an array of scientific challenges. We work as scientific partners and as service providers offering tailor-made solutions across a wide range of bioinformatics, statistics, and functional interpretation of data. We have an expanding team of computational biologists and software engineers that work multi-functionally across a wide variety of projects and disciplines, providing a supportive environment for our team to share knowledge and thrive.

PULSE-CF

The PULSE-CF Innovation Hub is a multi-centre multi-study initiative led by University of Manchester and funded by new award from CF Trust and LifeArc. The Hub is focussed on understanding the causes of exacerbations of CF and identifying ways to prevent these. Pulmonary exacerbations are a prominent feature of CF, though causes and pathophysiology remain poorly understood. This significantly restricts our ability to predict and prevent one of the most significant and burdensome aspects of CF. We propose that different types of exacerbation (i.e. endotypes) are determined by certain triggers and/or individual host factors such as airway microbiome composition and immune status and we aim deliver new mechanistic understanding of exacerbations and treatment response. This will allow us to establish an evidence-based clinical trial platform to test exacerbation prevention therapies, directly reducing harm from both exacerbations and antibiotics used as treatment. The post-holder will work across two studies.

Post Overview

The ideal candidate will have experience analysing multivariate datasets and will be able to code pipelines for data analysis independently. This could include the analysis and integration of omics datasets, including proteomics, metabolomics, transcriptomics (bulk and/or single cell analysis), and/or metadata analysis amongst others. The post-holder will be embedded into the clinical research hubs, thus engaging in the data evaluation and interpretation to its wider significance. You will be expected to liaise with clinical and experimental colleagues to advise on design, discussing findings, validation and dissemination of results.

You should have a PhD in systems biology, bioinformatics, computational biology or a relevant science discipline or have equivalent work experience. You should have a commitment to high quality research and be highly motivated to work in multidisciplinary teams.

Key responsibilities and duties:

• You will be responsible for the application of a wide array of computational biology methods on different datasets, particularly from omics technologies. You will be required to contribute to the contextual interpretation of the data.
• You will be required to liaise with the data manager to ensure data integrity throughout the data collection process remains to high standards.
• You will support experimental design best practices to ensure statistical analyses can be performed.
• To help plan, co-ordinate, develop and implement software pipelines for the analysis and integration of complex research datasets. This will include ensuring that code is adequately documented and adheres to best practices.
• To keep up to date with developments in computational biology research and apply the state-of-the-art analyses to projects.
• To write project reports to the highest possible standards to ensure simple transitions to publication quality output.
• To contribute to grant applications where required.
• You will be expected to publish your results in a peer-reviewed journal.
• Active participation in HUB meetings and CBF meetings and journal clubs as required.
• To communicate effectively between a wide range of stakeholders (clinicians, experimentalists, data scientists, etc.)
• To support the development and delivery of guided training within the teams and engage in outreach as required.
• To engage with other SRFs within LIV-SRF to ensure a fruitful transition from data generation to data analyses and outputs.
• To support publishing of data and code in appropriate repositories adhering to FAIR practices.
• To undertake administrative duties as required.
• Occasional travel to meet other stakeholders may be required.
• Ability to work with national CF data teams, and safely handle sensitive data as needed (according to GDPR).

All staff within HLS are encouraged to contribute to wider collegiality initiatives.

About you

Experience

• Experience in Bioinformatics or Computational Biology
• Experience of research in an academic or commercial environment
• Proven expertise and experience in statistical methods and analysis
• Experience with the analysis and interpretation of large datasets e.g. omics (e.g. linking to the wider biological question)
• Experience in writing scientific papers
• Experience in building predictive models
• Experience working as part of a team
• Experience managing complex projects
• Commitment for best practices and FAIR research
• Proven track record of research with expertise in bioinformatics and publications, commensurate with the stage in career
• Experience in network analysis and data integration
• Experience in data analysis pipeline development and version control
• Experience in proteomics
• Experience in metagenomics
• Familiarity with the use of machine learning algorithms (e.g. random forest, neural networks, etc.)
• Experience in grant proposals and application procedures
• Experience in metabolomics

Education, qualifications and training

• PhD in Bioinformatics / Systems Biology / Biological Science with experience in the application of bioinformatics techniques / or related data science discipline with interest to learn biology, OR equivalent work experience

Skills, general and specialist Knowledge

• Excellent written and spoken English
• Excellent interpersonal and communication skills, both written and verbal
• Excellent time management and organisational skills
• Good knowledge and professional experience of R (or other programming language such as Python and the willingness to learn R)
• Evidence of experience/knowledge using off the shelf omics analytical pipelines
• Excellent skills in scientific writing and a history of delivering oral presentations at national/international meetings
• Knowledge and/or experience in software development and deployment
• Knowledge of bioinformatics databases
• Experience of taking a significant role in relevant research networks, meetings/conferences and initiatives

Personal attributes

• Ability to communicate well, conveying ideas and concepts clearly and effectively with stakeholders of different backgrounds (wet scientists, clinicians, etc.)
• Highly motivated with ability to work Independently but also as part of a team, contributing to the development and growth of areas.
• Consistent ability to produce high quality/quantity of work
• Dependable, reliable and self-motivated with a professional approach to work.
• Highly organised.
• Enthusiasm for research
• Enthusiasm for computational biology applications and developments
• Enthusiasm for cystic fibrosis research

How to Apply

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Once you submit your application you will receive an automatic email acknowledgment. You can view your application at any time by clicking into the application history section of your account.

The recruiting department will endeavour to respond to each application. However, if you have not heard within six weeks of the closing date, please take it that your application has not been successful on this occasion.

The recruitment process will have two further steps with selected candidates invited to complete a short task and best submissions invited for interview.