Postdoctoral Fellow - Ewald Group

- Financial incentives: depending on circumstances, monthly family/marriage allowance of £272, monthly child allowance of £328 per child. Generous stipend reviewed yearly, pension scheme, death benefit, long-term care, accident-at-work and unemployment insurances
- Hybrid working arrangements
- Private medical insurance for you and your immediate family (including all prescriptions and generous dental & optical cover)
- Generous time off: 30 days annual leave per year, in addition to eight bank holidays
- Relocation package
- 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, child sick leave, generous parental leave, holiday clubs on campus and monthly family and child allowances
- Contract duration: This position is a 2 year contract possible for renewable
- Salary: UK Equivalent £3,307 per month (Total package will be dependant on family circumstances)
- 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-EBI, we strongly believe that inclusive and diverse teams benefit from higher levels of innovation and creative thought. We encourage applications from women, LGBTQ+ and individuals from all nationalities.
- Job location: This role is based in Hinxton, near Cambridge, UK. You will be required to relocate if you are based overseas and you will receive a generous relocation package to support you.

The Ewald Lab at EMBL-EBI is seeking a postdoctoral researcher to analyse a first-of-its-kind toxicology dataset. As members of the OASIS Consortium, which brings together 40 pharmaceutical/agrochemical companies, government agencies, academic labs and non-profit organizations, we aim to develop novel approaches for predicting liver toxicity to reduce reliance on animal testing and increase the accuracy of safety assessment. The dataset includes high-dimensional readouts including Cell Painting, transcriptomics, and proteomics. For one example of our early research directions, see this recent preprint.

Possible directions within this project include:

- Developing predictive models for compound mode-of-action using multi-omics data
- Using deep learning to extract features from:
- Public histopathology images and comparing them to OASIS-generated data
- OASIS-generated Cell Painting data and using them to investigate single-cell heterogeneity in compound-induced perturbations
- Investigating different mathematical approaches to extrapolate biological responses across in vitro and in vivo toxicity tests

EMBL-EBI is part of the European Molecular Biology Laboratory (EMBL) and is a world-leading bioinformatics centre providing biological data to the scientific community with expertise in data storage, analysis and representation. EMBL-EBI provides freely available data from life science experiments, performs basic research in computational biology and offers an extensive user training programme, supporting researchers in academic and industry.

You have

- A PhD or equivalent qualification in computer science, statistics, mathematics, physics, and/or engineering, or a degree in biological science with demonstrated computational experience.
- Strong programming skills, preferably in Python or R.
- Expertise in statistical methods, mathematical modelling, and/or machine learning.
- Proven ability to develop computational methods with applications in biology, preferably for high-dimensional data.
- Demonstrated ability to publish research in international peer reviewed journals.
- Excellent communication, collaboration, and leadership skills.
- The desire to be a supportive, creative, and responsible team member.

You may also have

- Expertise in computational toxicology or pharmacology, from either a pharmaceutical or regulatory perspective.
- Experience with computational image analysis or multi-omics integration.
- Experience with frameworks like PyTorch, Keras, Pyro or TensorFlow.

To apply please submit a cover letter and a CV through our online system before the closing date 02/04/2025