Research Fellow in Computational Metabolomics - School of BiosciencesGrade 7
Research Fellow in Computational Metabolomics - School of BiosciencesGrade 7
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
£ 36130 - 45413
1 Vacancy
Job Description
Position Details
School of Biosciences
Location: University of Birmingham Edgbaston Birmingham UK
Full time starting salary is normally in the range 36130 to 45413 with potential progression once in post to 48149
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 includingPrecisionTox andPARC (Partnership for the Assessment of Risks from Chemicals) in close collaboration with thePhenome 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 chromatographymass spectrometry (LCMS)-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 (MS) 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 Toxicologya 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 Unions Chemicals Strategy for Sustainability and the European Green Deals 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 LCMS-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 worlds 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 (MS) 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 (Bachelors/BSc) and postgraduate (Masters/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 (MS) 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 (Bachelors/BSc) and postgraduate (Masters/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 incomputational 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 LCMS and/or MS 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:
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 everyoneon our website.
Employment Type
Full-Time
