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Alex Persat

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Postdoctoral Position: Image-Based Drug Screening Against Bacterial Pathogens EPFL in Switzerland

Degree Level

Postdoc

Field of study

Computer Science

Funding

Competitive salary according to the EPFL postdoc salary scale; support for independent fellowship applications (EMBO, HFSP, MSCA) where relevant.

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Country

Switzerland

University

EPFL

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Keywords

Computer Science
Chemistry
Microbiology
Biomedical Engineering
Biophysics
Biology
Antibiotic Resistance
Medical Science
Pathogen Biology
Drug Screening
Phenotypic Screening
Physics
ML
bio engineering

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About this position

This postdoctoral project at EPFL is based in the laboratory of Prof. Alex Persat in the School of Life Sciences. The position focuses on building a new image-based drug screening platform to identify compounds active against major gram-negative bacterial pathogens, including Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa.

The researcher will design and implement a microscopy-based phenotypic screening workflow that combines live imaging, high-content screening, and single-cell/single-bacterium resolution. A major goal is to develop assays that can distinguish different phenotypes associated with compound activity, such as growth inhibition, biofilm or attachment disruption, and effects on membrane integrity.

The role also involves developing or adapting image analysis and quantification pipelines, with AI support, to manage screen-scale datasets. Screening hits will be followed up to determine their molecular targets or mechanisms of action using genetic, chemical-biology, or biophysical approaches, drawing on expertise within the lab and the broader research environment.

The successful candidate will work closely with the group’s discovery and design efforts, including natural products and AI-enabled molecular design, so that prioritised targets and hits can feed back into upstream compound design. The platform will be applied both in standard culture and, in collaboration with other lab members, in the group’s organoid and tissue-engineered infection models for airway and gut systems, with the aim of prioritising physiologically relevant hits.

The post includes opportunities to contribute to method development, data management, grant reporting, and co-supervision of PhD students. It is also embedded in the NCCR AntiResist consortium, giving access to a wider network of antimicrobial resistance researchers across Switzerland.

Funding details

Competitive salary according to the EPFL postdoc salary scale; support for independent fellowship applications (EMBO, HFSP, MSCA) where relevant.

What's required

Applicants should have a PhD in microbiology, biophysics, bioengineering, or a related field, completed or near completion, and at least one first-author publication. Hands-on experience with quantitative microscopy such as live-cell imaging, high-content screening, or single-cell/single-bacterium imaging is required. Candidates should be comfortable with image analysis pipelines and scripting in Python; experience integrating ML-based image analysis is a plus but not required. Interest in working across the interface of imaging, microbiology, and drug discovery is expected.

How to apply

Submit a cover letter of up to 2 pages describing your research interests, achievements, and fit, along with a CV including a publication list and contact details for 3 referees. Apply only through the EPFL careers portal. Informal inquiries may be sent to [email protected].

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Professors

Prof. at EPFL

University Name
Country flag

Switzerland

Research Interests

Microbiology

Physics

Drug Screening

Bio Engineering

Antibiotic Resistance