Postdoctoral Fellow - Bioinformatics & Executable Modelling for Rare Disease Digital Twins

European Molecular Biology Laboratory; Cambridgeshire and Peterborough; On-site; GBP 48,000 - 56,000; Full time

Job summary

Join a pioneering project at a leading research organization as a postdoctoral researcher. You will contribute to building Digital Twins for rare diseases using advanced modeling techniques, ultimately impacting the future of translational research. Collaborate closely with experts in systems biology and AI to drive innovation in rare disease research.

Benefits

Generous stipend reviewed yearly

30 days annual leave plus public holidays

Financial incentives including monthly allowances

Private medical insurance for you and family

Flexible working arrangements

On-site nursery and family benefits

Qualifications

• Experience with omics data analysis and integration.
• Ability to develop and fit executable models.
• Strong communication and teamwork skills.

Responsibilities

• Generate networks from bulk-RNAseq and scRNAseq data.
• Build executable models from omics data.
• Collaborate with data curators and multi-omics scientists.

Skills

Python

Data analysis

Teamwork

Communication

Education

PhD in bioinformatics, physics, or related field

Job description

We are looking for a motivated and talented postdoctoral-level researcher with experience in executable modelling to join a cutting-edge project developing Digital Twins for rare diseases. This is a unique opportunity to work at the intersection of systems biology, AI, and translational research, and to contribute to open science through the Chan Zuckerberg Initiative.

Your group
Petsalaki Group, in collaboration with Open Targets and BioModels teams.

The project
Digital Twins are virtual representations of patients that simulate disease progression and treatment response. Rare diseases pose a unique challenge due to limited patient data-especially at the single-cell level-making traditional modelling approaches difficult. This project tackles that challenge by integrating multi-omics and clinical data using hybrid models combining mechanistic, GenAI, and machine learning approaches.

You'll contribute to building disease-specific Digital Twins using large-scale single-cell multi-omics datasets, mechanistic simulations, and predictive AI models. Your work will help unlock new insights into disease mechanisms and inform potential treatments, diagnostics, and drug repurposing opportunities.

Your role
You will develop and apply methods to transform omics data into networks and executable models, collaborating closely with experts across the Petsalaki and Sheriff groups, Open Targets, EMBL-EBI, and the wider rare disease and biocuration community. You will be primarily supervised by the Petsalaki group (Whole cell sigalling) and the Sheriff team (Biomodels). The Petsalaki group develops data driven network inference and modelling approaches from large omics datasets and the Sheriff team leads the development of innovative modelling approaches and maintenance of the Biomodels database.

Key responsibilities include:

• Generation of phenotype-specific networks from bulk-RNAseq and scRNAseq data from rare disease patients
• Building executable models (Boolean, ODE, agent-based or others) from omics data
• Collaborating closely with data curators, multi-omics data scientists and AI engineers to integrate and enrich disease datasets, and test and validate models
• Applying hybrid modelling approaches to limited data scenarios
• Enabling multi-scale and cross-disease modelling for hypothesis generation and therapy discovery
• Ensure FAIR principles in your outputs and contribute to the open source community by sharing models (where possible) in BioModels and other repositories
• Generation of synthetic data to represent rare disease patients that can be shared

You have

• A PhD in bioinformatics, physics, or a related data-intensive field
• Proficiency in Python (or R), version control, and clean code practices
• Experience with omics data analysis and integration
• Hands-on expertise in developing and fitting executable models
• Strong communication and teamwork skills

You may also have

• Network inference and analysis experienc
• Machine learning experience
• Track record of completed research projects (e.g., publications, tools)

Contract length: 2 years fixed-term grant-limited. This position is funded by the Chan Zuckerberg Initiative (CZI) grant.

Salary: Year 1 Stipend at rate of £3,307 per month after tax but excluding pension and insurance contributions.

Interviews: We plan to hold interviews on 24th of July. If you are selected for a final interview, you will be asked to give a presentation. Details will be confirmed with selected candidates.

This is a high-impact role with the potential to shape the future of rare disease research. Join us to push the boundaries of what's possible in computational biology and personalised medicine.

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 if you're overseas

What else you need to know

• International applicants: We recruit internationally and successful candidates are offered visa exemptions. Read more on our page for international applicants.
• Diversity and inclusion: At EMBL, we strongly believe that inclusive and diverse teams benefit from higher levels of innovation and creative thought. We encourage applications from women, LGBTQ+ & individuals from all nationalities.
• Job location: All our fellowships are based on-site (for at least part of each week). If you are living overseas, you will receive a generous relocation package to support you.
• EMBL is a signatory of DORA. Find out how we apply DORA principles to our recruitment and performance assessment processes here.
• Watch this video to find out what it's like to be a Postdoc at EMBL-EBI.
• How to apply: To apply please submit a cover letter and a CV through our online system. Applications will close at 23:59 CET on the date shown below. We aim to provide a response within two weeks after the closing date below.

Closing Date
13/07/2025