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Postdoctoral Fellow

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About the team/job

Cell plasticity is considered a key hallmark of metastatic cells and cancer therapy resistance by enabling cell adaptation to adverse conditions. Molecular and cellular mechanisms underlying cell plasticity are still poorly understood and a precise description of cell plasticity remains to reach consensus, mainly due to a lack of technologies that enable to quantitatively assess it. This project, entitled “A multiplexed biomimetic imaging platform for assessing single-cell plasticity and scoring of tumour malignancy” (PLAST_CELL) is funded by the European Innovation Commission (Project ID 101046620), and aims at developing a radically new approach to assess cancer cell plasticity as a predictive index of tumour aggressiveness.

The Uhlmann group develops methods to quantify morphology from microscopy images, whether they are 2D, 3D, static, dynamic, and of any imaging modality. Our overarching aim is to provide general quantification frameworks for bioimages to investigate living systems across scales and build bridges between mathematical modeling and image data. In the PLAST_CELL project, we will lead the image analysis and modeling efforts, teaming up with our 3 academic partners based in Spain (CRG – project lead, IMIM, ICFO) and industry partner based in France (Cherry Biotech). 

Your role

The successful candidate will develop a novel image analysis pipeline to extract morphodynamic features from image data, and exploit state-of-the-art machine learning techniques to aggregate them with cancer cell models based on in vitro assays, in vivo metastasis experimental assays, and clinical patient outcomes.

The image analysis pipeline will be optimized to retrieve precise morphological descriptors in combination with molecular features of cancer cell dynamics in 3D micro-environments. An important task will be to analyze how these dynamical readouts combine with the temporal evolution and time of response of the morphological metrics. This work will also involve designing a predictive model of tumour aggressiveness based on the extracted morphodynamic features. The model will aim to be predictive of prototypic cancer cell types and patient data, and will be tested through patients’ cancer malignancy classification experiments.

We expect all code produced in this project to be developed in Python, released as fully open source, and made publicly available to the research community along with analysis results following reproducible research practices. 

You have

  • A PhD in computational biology, bioinformatics, or data science.
  • Hands-on experience with image processing and analysis. 
  • Solid expertise in the Python programming language, with previous experience developing Python-based analysis pipelines. 
  • Interest in cancer biology with medical applications.
  • Previous research experience involving the use of state-of-the-art machine learning.
  • Prior experience with biostatistics.
  • Independent and motivated work habits and excellent verbal and written communication skills in English.
  • Strong communication skills necessary for inter-institutional and international collaborations.  

You might also have

  • Experience managing (archiving and sharing) large biomedical datasets.
  • Hands-on experience with generative modelling.
  • Hands-on experience with Python-based open-source bioimage analysis platforms such as napari.  

Why join us

Do something meaningful
At EMBL-EBI you can apply your talent and passion to accelerate science and tackle some of humankind’s greatest challenges. EMBL-EBI, part of the European Molecular Biology Laboratory, is a worldwide leader in the storage, analysis and dissemination of large biological datasets. We provide the global research community with access to publicly available databases and tools which are crucial for the advancement of healthcare, food security, and biodiversity.

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 benefits:

  • Financial incentives: Monthly family and child allowances, generous stipend reviewed yearly, pension scheme, death benefit, long-term care, accident-at-work and unemployment insurances
  • Flexible 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
  • 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, 10 days of child sick leave, generous parental leave, holiday clubs on campus and monthly family and child allowances
  • Benefits for non-UK residents: Visa exemption, education grant for private schooling, financial support to travel back to your home country every second year and a monthly non-resident allowance.

For more details, please see our employee benefits page

What else you need to know

  • Contract duration: This position is limited to the project duration of 3 years or until 30.04.2026, whichever is shortest.
  • 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.
  • How to apply: To apply please submit a cover letter and a CV through our online system. We aim to provide a response within two weeks after the closing date.
  • DORAEMBL is a signatory of DORA and is committed to hiring and training outstanding research, service, and administrative personnel.

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