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Michaela Wenzel

6 months ago

Doctoral student in AI-driven prediction of antimicrobial mechanisms of action Chalmers University of Technology in Sweden

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Expired

Country flag

Country

Sweden

University

Chalmers University of Technology

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Keywords

Computer Science
Machine Learning
Chemistry
Biomedical Engineering
Biology
Predictive Modeling
Spectroscopy
Microscopy
Computational Biology
Systems Biology
Medical Science
Pathogen Biology
Omics
Antimicrobial Peptide
Statistics
Bioinformatic

About this position

Chalmers University of Technology invites applications for a fully funded doctoral student position in AI-driven prediction of antimicrobial mechanisms of action, based in the Division of Molecular Bioscience, Department of Life Sciences. This position is part of the prestigious Data-driven Life Science (DDLS) program, a national initiative funded by the Knut and Alice Wallenberg Foundation, aiming to advance computational and data science capabilities in Sweden. The DDLS program focuses on four strategic research areas: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, and epidemiology and biology of infection.

The doctoral student will join the Antibiotic Research Group led by Associate Professor Michaela Wenzel and be integrated into the Computational Systems Medicine Group led by Annikka Polster. The research project, "Towards a mechanism-aware multi-label prediction framework for antimicrobial peptides," centers on using mechanistic data to connect the structure of antimicrobial peptides (AMPs) to their function and activity. AMPs are potent molecules with broad-spectrum antibacterial, antibiofilm, antifungal, antiviral, antiparasitic, and immunomodulatory properties, making them promising alternatives to traditional antibiotics.

The project addresses a challenging data and modelling problem: building predictive frameworks when training labels are systematically mislabelled. The team has access to three unique curated datasets combining multi-omics, microscopy, and spectroscopy data, providing a robust foundation for machine learning approaches. The doctoral student will focus on ontology-informed dataset integration, multi-label model development, systematic benchmarking, and biological validation. The work is primarily computational, but opportunities for experimental validation are available during model validation phases.

Applicants must hold a Master's degree (120 credits) or a Master’s degree (60 credits) in a life science or data science-related discipline, or a 4-year Bachelor’s degree if earned outside Sweden. Experience in data science, computational biology/medicine, bioinformatics, AI, or related areas is required. Programming skills are mandatory, and proof must be provided by the project start if not at application. Strong written and verbal communication skills in English, an interdisciplinary and collaborative mindset, and the ability to work across disciplines are essential. Candidates with strong machine learning or data science backgrounds and limited bioscience experience are encouraged to apply; biological knowledge can be acquired during PhD coursework. Candidates without significant computational background will only be considered in exceptional cases.

The position is fully funded from the start, with a starting salary of 34,550 SEK per month (valid from May 25, 2025). The appointment is fixed-term for four years, with the possibility to teach up to 20%, which can extend the position up to five years. Doctoral studies require physical presence throughout the study period, and a valid residence permit must be presented by the study start date. As a doctoral student at Chalmers, you are an employee and enjoy all employee benefits, including a dynamic working environment in Gothenburg, generous parental leave, subsidized day care, free schools, and healthcare. Chalmers is committed to gender balance, equality, and inclusion, offering Swedish courses for non-native speakers.

To apply, submit your application in English as PDF files via the provided application form. Include your CV, personal letter, motivation, and transcripts for Bachelor’s and Master’s thesis. Incomplete applications and those sent by email will not be considered. References will be requested after the interview. The application deadline is 31 May 2026, with interviews expected in June and a planned start date in October 2026. For questions, contact Associate Professor Michaela Wenzel at [email protected].

Chalmers University of Technology is a leading institution in technology and natural sciences, fostering innovation and scientific excellence for a sustainable world. Join us in advancing the future of data-driven life science!

Funding details

Available

What's required

Applicants must have a Master's degree (120 credits) or a Master’s degree (60 credits) in a life science or data science-related discipline, or a 4-year Bachelor’s degree if earned outside Sweden. Experience in data science, computational biology/medicine, bioinformatics, AI, or related areas is required. Programming skills are mandatory (proof required by project start if not at application). Strong written and verbal communication skills in English, interdisciplinary and collaborative mindset, and ability to work across disciplines are essential. Candidates with strong ML or data science backgrounds and limited bioscience experience are encouraged to apply; biological knowledge can be acquired during PhD coursework. Candidates without significant computational background will only be considered in exceptional cases. Physical presence required throughout study period; valid residence permit must be presented by study start date.

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Professors

Associate Professor at Chalmers University of Technology

University Name
Country flag

Sweden

Research Interests

Microbiology

Cell Biology

Antimicrobial Peptide

Pathogen Biology

Antibiotic Discovery