Job Specifications
Your group
The Petsalaki, Saez-Rodriguez (EMBL-EBI) and Korcsmáros (Imperial College) groups develop cutting-edge computational and AI approaches to unravel cellular signalling and gene regulation from large-scale omics data. Our research combines systems biology, network modelling, and data-driven inference to understand disease mechanisms and guide therapeutic discovery.
Your supervisor
You will be supervised by Dr. Evangelia Petsalaki, along with Dr. Tamas Korcsmáros and Prof. Julio Saez-Rodriguez, in close collaboration with academic and industry partners of the Open Targets consortium.
Your role
Join us to build the next generation of tools that connect multi-omics data to disease mechanisms. As part of the NetworkCommons project, an ambitious Open Targets initiative, you will help create an open, community-driven platform that transforms how researchers interpret biological networks and identify new therapeutic targets. A pilot version of the project can be found here: https://academic.oup.com/bioinformatics/article/41/2/btaf048/8002097
You will benchmark and integrate state-of-the-art network contextualisation methods, combining large-scale transcriptomics, proteomics, and single-cell data across key disease areas including oncology, inflammatory bowel disease, and neuroinflammation. Working closely with developers and industry partners, you will contribute to a resource that will shape how network biology is applied in drug discovery and translational research.
You have
A PhD in computational biology, bioinformatics, computer science, or a related quantitative discipline
Strong experience in omics data analysis and/or development of computational methods
Ability to understand the data and interpret the results is important
Proficiency in Python and/or R, and ideally also familiarity with reproducible workflows (e.g. Nextflow, Snakemake)
A strong understanding of molecular or systems biology
Excellent communication skills and enthusiasm for collaborative, interdisciplinary research
You may also have
Expertise in network biology, graph algorithms, or causal inference
Experience benchmarking bioinformatics tools or integrating multi-omics datasets
Familiarity with containerisation (Docker, Singularity)
Interest in open science and building tools with real-world translational impact
Contract length: 3-year grant limited fixed term contract.
Salary: For individuals who have obtained their PhD, the Year 1 Stipend rate is applied at £3,383.52 per month after tax but excluding pension and insurance contributions.
For individuals who are yet to be awarded their PhD, an initial predoctoral rate will apply at £2,436.14 per month after tax but excluding pension and insurance contributions.
Next Steps
This vacancy has a scheduled closing date of 17th December - We invite you to submit your application as soon as possible. Please include both your up-to-date CV and cover letter.
Should you be selected to be invited to interview, we will ask for two letters of recommendation to be provided ahead of your scheduled interview date.
Professional development support
The EMBL Fellows’ Career Service provides support and guidance to predoctoral and postdoctoral fellows across all six EMBL’s sites.
Working with a dedicated Careers Advisor, this invaluable service will help you to take informed decisions about your career planning both in the short and longer term. Whether your main interest is pursuing a career path in academia, exploring opportunities in industry or exploring an independent venture, the EMBL Fellows’ Career Service with provide you with a portfolio of activities and resources to help you.
To find out more please visit - EMBL-fellows-career-service
Why join us
Join a culture of innovation
We are located on the Wellcome Genome Campus, alongside other prominent research and biotech organisations, and surrounded by beautiful Cambridgeshire countryside. This is a highly collaborative and inclusive community where our employees enjoy a relaxed atmosphere. We are committed to ensuring our employees feel valued, supported and empowered to reach their professional potential.
Enjoy Lots Of Employee Benefits
Financial incentives: Monthly family and child allowances, generous stipend reviewed yearly, pension scheme, death benefit and unemployment insurances
Flexible working arrangements including hybrid working patterns
Private medical insurance for you and your immediate family
Generous time off: 30 days annual leave per year in addition to public holidays
Campus life: Free shuttle bus to and from work, on-site library, subsidised on-site gym and cafeteria, casual dress code, extensive sports and social club activities (on campus and remotely)
Family benefits: On-site nursery (Heidelberg & Hinxton), 10 days of child sick leave, paid maternity & parental leave, holiday clubs on campus and monthly family and child allowances
Benefits for non-residents: Visa and financial support to relocate i