Research Associate

Contract Type: Fixed Term contract up to May 2026

Background

The Research Assistant role will develop computational pipelines and perform data analysis for the EU Partnership for the Assessment of Risks from Chemicals (PARC) project, and other associated projects, activities and research.

This role will collaborate with Principal Investigators, postdoctoral researchers, and PhD students on the EU PARC and related projects. The primary responsibility of this position is to develop comprehensive machine learning and artificial intelligence (AI) pipelines for single- and multi-omics modelling and prediction. Working under PI supervision, the role will focus on (but not limited to) implementing graph neural networks, network biology approaches, multimodal learning techniques, and explainable AI methodologies.

Role Summary

The post holder will perform data pre-processing and analysis using both the developed computational pipelines and existing bioinformatics and biostatistics tools for the EU PARC and associated projects. The Research Assistant will be responsible for summarising computational results and scientific findings, and contributing to relevant research publications. In addition, the position involves assisting the PIs to provide supervision to Master's-level research projects related to the core research areas.

Furthermore, the Research Assistant will actively participate in regular team meetings and present findings. The role requires maintaining comprehensive documentation of all code, analytical methods, and procedures to ensure reproducibility and knowledge transfer. The post holder will assist with project management aspects including tracking milestones, managing timelines, and contributing to technical reports for the EU PARC project. Additionally, the Research Assistant will be responsible for implementing robust data management practices, ensuring proper organisation and storage of research data while maintaining compliance with relevant data protection regulations and institutional policies.

Main Duties

• Develop and implement machine learning and AI pipelines for single- and multi-omics modelling and prediction, with emphasis on graph neural networks, network biology, multimodal learning, and explainable AI approaches.
• Conduct data pre-processing, integration, and analysis using developed pipelines and established bioinformatics and biostatistics tools for the EU PARC and related projects.
• When needed, collect additional research data from public databases and existing publications to support omics analyses.
• Summarise computational results and scientific findings in a clear, accessible format as directed by Principal Investigators.
• Present research outputs through various channels, including drafting sections of scientific publications and delivering presentations at team meetings.

Person Specification

• Received a Master’s degree or equivalent in bioinformatics, computational biology, or similar subject areas. 
• Proficiency in data science, machine learning, and AI, particularly in graph neural networks, network biology, explainable AI, and multimodal learning. 
• Experience in applying data science, machine learning, and AI techniques to analyse both single- and multi-omics data, with a focus on transcriptomics and metabolomics.
• Skills in Python and R programming, with knowledge of established bioinformatics, biostatistics, data sciences, machine learning and AI packages. 
• Ability to manage scientific resources, e.g. data, source codes, and result files, and access public resources.
• Ability to manage research project and communicate effectively.

Informal enquiries to Professor Luisa Orsin, email: l.orsini@bham.ac.uk and Dr Jiarui Zhou, email: j.zhou.3@bham.ac.uk

To download the full job description and details of this position and submit an electronic application online please click on the 'Apply' button above.

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