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Postdoctoral Fellow in AI-Based Protein Design and Synthetic Biology for De Novo Biofilm Systems Lund University in Sweden
Degree Level
Postdoc
Field of study
Computer Science
Funding
Full-time, fixed-term postdoctoral employment for a maximum of 2 years. Salary is monthly salary; no stipend amount is stated. Teaching may be included up to 20% of working hours, with three weeks of training in higher education teaching and learning.
Deadline
Oct 31, 2026
Country
Sweden
University
Lund University

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About this position
Postdoctoral Fellow in AI-Based Design of De Novo Protein Biofilm Systems at Lund University, Sweden.
This postdoctoral position sits at the intersection of AI-based protein design, synthetic biology, biofilm engineering, and programmable living materials. The project focuses on the de novo design of protein biofilm systems and combines computational protein design with experimental biology to create new molecular functions and mechanisms for controlling the formation, organization, and properties of living materials.
Research activities may include development and application of AI-based protein design methods, experimental characterization of designed proteins, microbial engineering, biofilm design, and high-throughput functional screening. The role is research-focused, with teaching allowed up to 20% of working time and three weeks of training in higher education teaching and learning included.
The position is hosted at Lund University’s Faculty of Science and is linked to a translational research environment with entrepreneurship potential. The lab notes that its first spinout company is already funded and operational, with additional translational opportunities under development.
Eligibility highlights: applicants must hold a PhD or equivalent degree in a relevant field, completed within the last three years unless special circumstances apply. Strong English proficiency is required. Preferred experience includes computational or de novo protein design, synthetic biology, microbial or yeast engineering, biofilm engineering, high-throughput screening, automation, and computational pipelines for biological design.
Funding/employment: full-time, fixed-term employment for up to 2 years. Salary is monthly; no stipend amount is listed.
Application deadline: 2026-10-31.
How to apply: submit an English-language PDF application including a CV with publications, a short research statement (past and future interests, max three pages), contact details for at least two references, and copies of the doctoral degree certificate and other relevant transcripts/certificates. Apply via the online portal.
Funding details
Full-time, fixed-term postdoctoral employment for a maximum of 2 years. Salary is monthly salary; no stipend amount is stated. Teaching may be included up to 20% of working hours, with three weeks of training in higher education teaching and learning.
What's required
Applicants must have a PhD or equivalent degree in a subject relevant to the position, completed no more than three years before the employment decision unless special circumstances apply. Very good oral and written English is required. Relevant backgrounds include protein design, computational biology, structural biology, synthetic biology, biotechnology, bioengineering, microbiology, molecular biology, or closely related fields. Strong research qualifications, independence, interdisciplinary collaboration ability, and teaching skills are important; additional experience in AI-based protein design, experimental protein characterization, microbial or yeast engineering, biofilm engineering, high-throughput screening, automation, and computational pipelines is highly valued.
How to apply
Prepare a PDF application in English containing a CV with publications, a description of past research and future interests (max three pages), contact details for at least two references, and copies of the doctoral degree certificate and other relevant certificates/grades. Submit through the university's online application portal before the deadline.
More information can be found here
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