Research Fellow in Computational Metabolomics - School of Biosciences - 105468 - Grade 7

Position Details

School of Biosciences

Location: University of Birmingham, Edgbaston, Birmingham UK

Full time starting salary is normally in the range £36,130 to £45,413 with potential progression once in post to £48,149

Grade: 7

Full Time, Fixed Term contract up to August 2028

Closing date: 15th July 2025

Background

We are seeking an innovative Research Fellow in Computational Metabolomics to join the Centre for Environmental Research and Justice (CERJ) and the School of Biosciences at the University of Birmingham. You will be working in a vibrant, interdisciplinary research ecosystem, driving cutting-edge research at the intersection of metabolomics, human health, and toxicology. This exciting role offers the opportunity to contribute to major EU-funded research programmes, including PrecisionTox and PARC (Partnership for the Assessment of Risks from Chemicals), in close collaboration with the Phenome Centre Birmingham. These programmes are advancing the science and practice of chemical risk assessment and informing next-generation regulatory frameworks to better protect human health and the environment from toxic substances.

Specifically, the post holder will develop, implement, and apply advanced computational tools and reproducible workflows to interrogate large-scale, liquid chromatography–mass spectrometry (LC–MS)-based comparative metabolomics datasets spanning a range of model organisms (e.g. Danio rerio, Caenorhabditis elegans, Drosophila melanogaster, Daphnia magna, and others) and human cell lines. In addition, the role will involve the in-depth characterisation and annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based approaches, machine learning) where appropriate. The successful candidate will actively promote FAIR data practices and will have opportunities to contribute to teaching, training, and wider community engagement.

Research team:

• The role is embedded within a diverse and interdisciplinary research environment comprising experienced scientists in toxicology and human health, analytical chemistry, software engineering, statistics, and bioinformatics.
• The successful candidate will join a team with a strong track record in developing computational tools and informatics infrastructure for metabolomics applications in toxicology, systems biology, and human and environmental health.
• Close collaboration is expected with colleagues in he Phenome Centre Birmingham, as well as with national and international partners across academia and industry.

Relevant projects or entities:

• PrecisionTox, coordinated by the University of Birmingham and involving 15 European and US partners, seeks to revolutionise chemical safety assessment through the development of Precision Toxicology—a data-driven approach that reduces reliance on animal testing, lowers uncertainty, and enhances protection of human health.
• PARC (Partnership for the Assessment of Risks from Chemicals) aims to develop next-generation chemical risk assessment to protect human health and the environment. It supports the European Union's Chemicals Strategy for Sustainability and the European Green Deal's “Zero pollution” ambition with new data, knowledge, methods and tools, expertise and networks.
• The Phenome Centre Birmingham (PCB) is an internationally recognised metabolomics centre, offering consultancy research services to academic, industry, and government partners. The centre provides expertise and advice in metabolomics research, from conception and experimental design through data acquisition to data analysis and biological interpretation.

Role Summary

• Develop, implement, and apply advanced reproducible computational tools and workflows to process, analyse, and interpret large-scale LC–MS-based comparative metabolomics datasets. These datasets, spanning a range of model organisms (e.g. Danio rerio, Caenorhabditis elegans, Drosophila melanogaster, Daphnia magna, etc) and human cell lines, represent one of the world’s most comprehensive toxicological cross-species metabolomics resources.
• Drive the in-depth computational characterisation and annotation of metabolomes across diverse model organisms and human cell lines, using multistage fragmentation (MSⁿ) data and computational methods and approaches (e.g. spectral matching, network-based approaches, and machine learning techniques, etc).
• Design and apply robust statistical analysis strategies to uncover biologically meaningful patterns from complex metabolomics datasets, support hypothesis testing, and enable cross-species comparisons of metabolic responses to chemical exposures or other perturbations.
• Actively promote and uphold FAIR (Findable, Accessible, Interoperable, Reusable) data practices, ensuring that all workflows, datasets, and code are transparent, well-documented, reproducible, and openly shared with the scientific community.
• The role also offers opportunities to contribute to teaching and training activities across undergraduate (Bachelor’s/BSc) and postgraduate (Master’s/MSc) programmes, mentor early-career researchers, and engage with dynamic, interdisciplinary networks involving academic, industrial, and regulatory partners.

Main Duties

• Improve, develop, implement, and apply advanced computational tools and workflows to process, analyse, and interpret large-scale LCMS-based metabolomics datasets across multiple species and experimental conditions.
• Drive the characterisation and annotation of metabolomes using multistage fragmentation (MSⁿ) data, developing and employing a wide range of approaches and methods (e.g. spectral matching, network-based approaches, and machine learning).
• Generate and maintain high-quality documentation, including detailed scientific reports and user guides for developed tools and workflows.
• Troubleshoot and resolve challenges affecting data quality, analysis workflows, or research outcomes, working independently or in collaboration with colleagues.
• Ensure that all computational tools, workflows, and data outputs are robust, version-controlled, and reproducible, adhering to FAIR (Findable, Accessible, Interoperable, Reusable) principles.
• Disseminate research findings through journal publications, conference presentations, workshops, internal reports, and web-based resources.
• Curate, manage, and submit metabolomics datasets to local and international data repositories, ensuring quality control and comprehensive metadata annotation.
• Contribute to the delivery of lectures and practical sessions for undergraduate (Bachelor’s/BSc) and postgraduate (Master’s/MSc) programmes (or similar), particularly in areas such as metabolomics, bioinformatics, and toxicology.
• Collaborate with interdisciplinary teams across academia and collaborators to advance the aims and objectives of projects such as PrecisionTox and PARC.
• Support the preparation of grant proposals and funding bids related to metabolomics, computational biology, and toxicology.
• Promote equality, diversity, and inclusion, and contribute to creating an open and welcoming research environment.
• Apply knowledge in a way which develops new intellectual understanding.
• Contribute to developing new models, techniques and methods.

Person Specification

Qualifications and Training

• PhD (awarded or near completion) or equivalent experience in computational or mass spectrometry-based metabolomics, bioinformatics, or a related discipline.
• Demonstrated commitment to ongoing professional development in one or more of the above disciplines.

Technical Knowledge and Experience

• Strong expertise in the processing, analysis, and interpretation of LC–MS and/or MSⁿ data using open-source and commercial tools (e.g. XCMS, MZmine, Compound Discoverer, GNPS, SIRIUS, etc).
• Proficiency in one or more programming languages (e.g. R, Python).
• Experience with continuous integration and best practices in code development and maintenance (e.g. Github/Gitlab, GitHub Actions, etc).
• Experience with machine learning or network-based approaches is desirable.
• Familiarity with FAIR data principles and experience in developing reproducible and well-documented computational workflows and analysis (e.g. Jupyter, RMarkdown, Galaxy, Snakemake, or Nextflow).
• Understanding good practice in research data stewardship.
• Knowledge of toxicology or human/environmental health would be an advantage.

Interpersonal and Teamwork Skills

• Excellent communication skills, including the ability to clearly present complex technical data to a range of audiences.
• Proven ability to work collaboratively within multidisciplinary and/or national and international teams.
• Experience mentoring students or early-career researchers is desirable.

Personal Attributes and Working Style

• Highly organised, with the ability to manage multiple tasks and priorities simultaneously.
• A high level of accuracy and attention to detail.
• Capable of working independently and proactively, including time management.
• Enthusiastic, adaptable, and able to contribute positively to a dynamic and fast-paced research environment.
• Knowledge of the protected characteristics of the Equality Act 2010, and how to actively ensure in day to day activity in own area that those with protected characteristics are treated equally and fairly.

Informal enquiries to Ralf Weber, email: r.j.weber@bham.ac.uk 

We believe there is no such thing as a 'typical' member of University of Birmingham staff and that diversity in its many forms is a strength that underpins the exchange of ideas, innovation and debate at the heart of University life. We are committed to proactively addressing the barriers experienced by some groups in our community and are proud to hold Athena SWAN, Race Equality Charter and Disability Confident accreditations. We have an Equality Diversity and Inclusion Centre that focuses on continuously improving the University as a fair and inclusive place to work where everyone has the opportunity to succeed. We are also committed to sustainability, which is a key part of our strategy. You can find out more about our work to create a fairer university for everyone on our website.