Postdoctoral Fellow Uhlmann Research Group

About the team/job

Chronic kidney failure affects about 11% of the world population, of which one-third of cases involve immune-mediated disease. Those patients who reach end-stage kidney failure require renal replacement therapy, and though transplantation considerably improves the quality of life, the longevity of transplant organs is limited, mainly due to immune rejection. Understanding which immune cells are important in the early response to antibodies, and the mechanisms by which they cause injury, underpins the development of effective future therapies. However, to do this, we need to develop better microscopy methods that are capable of imaging all immune cells within human biopsies, and powerful analysis methods to quantify these images. In this project funded by the MRC initiative for multimodal research across scales to understand human disease, we will explore the early and late stages of the immune reaction, with the ultimate goal of increasing the lifespan of transplanted kidneys.

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 this project, we will lead the image quantification and data integration efforts, teaming up with our partners from the Crick Institute (project lead), EMBL Heidelberg, EMBL Hamburg, and Imperial College London. 

Your role

The successful candidate will develop the computational tools required to extract quantitative information on the visual features of kidney transplant rejection across different imaging modalities, and integrate them into a predictive model.

Several image analysis workflows will need to be designed to extract the information contained in the image data and molecular readouts acquired in the project. Among others, it will involve a pipeline to automatically segment instances of immune and endothelial cells in volumetric electron microscopy images, and a pipeline to automatically detect structural features of interest in high-resolution high throughput tomography images. Once objects of interest are identified or segmented, an important task will be to extract a representation of morphology that is sufficiently rich to infer cell or structure identity, as validated with spatial omics data. Ultimately, the aim is to quantify the wealth of visual information contained in the image data generated in this project in such a way that it becomes possible to combine it into a single multimodal latent representation of antibody-mediated kidney transplant rejection.

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 or computer science.
• Solid expertise in modern deep learning strategies.
• Hands-on experience with image processing and analysis. 
• Hands-on experience using state-of-the-art machine learning algorithms.
• Solid expertise inthe Python programming language, with previous experience developing Python-based analysis pipelines. 
• Prior experience with deep learning libraries (PyTorch preferred).
• Interest in biological research with medical applications.
• Independent and motivated work habits and excellent verbal and written communication skills in English.
• Strong communication skills, as necessary for inter-institutional and international collaborations. 

You might also have

• Experience handling large image datasets.
• Hands-on experience with representation learning and generative modeling.
• Hands-on experience with Python-based open-source bioimage analysis platforms such as napari. 

Why join us

Do something meaningful
At EMBL-EBIyou 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 theWellcome 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 and financial support to relocate if you are based overseas. 

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. Ideally candidate must be available immediately.  
• 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. Recruitment process will take place online via Zoom and it's likely to include a seminar, panel and technical interviews and an opportunity to meet some of the group members and collaborators. 
• DORA - EMBL is a signatory of DORAand is committed to hiring and training outstanding research, service, and administrative personnel.