Postdoctoral Position in Biochemistry (Lund University)

Institution: Lunds universitet, Kemiska institutionen, Tillämpad biokemi Type of employment: Full-time, Temporary (3 years) Start date: 1 March 2026 or as agreed Reference number: PA2025/3203 City: Lund County: Skåne län Country: Sweden About Lund University Founded in 1666, Lund University is consistently ranked among the world’s top universities, with approximately 47,000 students and over 8,800 staff across Lund, Helsingborg, and Malmö. Lund University is committed to gender equality, diversity, and inclusive academic excellence. Description of the Workplace The Saragovi Lab at Lund University is part of the Division of Applied Biochemistry within the Department of Chemistry. The lab focuses on combining computational methods, Artificial Intelligence (AI), and high-throughput experimentation to systematically design protein-semiconductor hierarchical materials and de novo hierarchical architectures with atomic precision. This postdoctoral project aims to design de novo proteins that self-assemble into defined architectures and guide the formation of semiconductor materials with sub-nanometer precision. The position is highly interdisciplinary, involving collaboration between the Departments of Chemistry and Physics, the Center for Molecular Protein Science (CMPS), and semiconductor characterization teams within NanoLund. The Saragovi Lab offers access to: Substantial computational resources (GPU nodes) Advanced high-throughput instruments (FACS, mass photometer, ITC, SPR, etc.) State-of-the-art characterization tools (high-resolution TEM, ellipsometry, clean-room facilities) This setup allows a strong computational–experimental feedback loop central to the project. Subject Description Recent breakthroughs in deep learning–powered protein design (recognized by the 2024 Nobel Prize in Chemistry) now enable creation of proteins with near-atomic accuracy. Models such as RFdiffusion, LigandMPNN, and hallucination-based frameworks generate symmetric oligomers, cages, and backbones while optimizing sequence properties. This project focuses on designing proteins that act as templates for inorganic interfaces, forming symmetric oligomers to control inorganic material polymorph, facet composition, and geometry. The goal is to establish a design framework for programmable, functional protein–semiconductor metamaterials, contributing to sustainable biofabrication of (opto-)electronic nanotechnology. Work Duties The main duties of the postdoctoral position include conducting research, with teaching limited to a maximum of 20% of working hours. Responsibilities include: Developing computational protein design pipelines for: Volumes – symmetric or Janus assemblies that encapsulate defined voids Interfaces – templates and catalytic motifs that guide semiconductor formation Pores – structures that regulate selective entry of metal species Inert surfaces – stable outer assemblies in supersaturated solutions Performing high-throughput expression and screening of designed proteins to evaluate structural and functional quality Conducting experimental characterization of hybrid soft–hard hierarchical materials Collaborating with CMPS and NanoLund teams across chemistry, biophysics, and semiconductor science Contributing to grant applications and external funding acquisition Handling administrative tasks related to research activities Qualification Requirements Applicants must have a PhD (or equivalent international degree) in biochemistry, biophysics, chemistry, computational biology, or a related field. Priority is given to candidates who obtained their PhD within the last three years. Essential qualifications: Strong research skills and ability to conduct high-quality research independently Very good oral and written English proficiency Solid coding foundation for developing computational protein design pipelines Basic biochemical laboratory experience Ability to work independently and collaboratively in a multidisciplinary research environment Openness to learning and applying new computational and experimental methods Passion for tackling challenging design problems Additional qualifications (advantageous but not required): Extended knowledge of inorganic and organic chemistry Experience in deep learning model development or computational protein design Experience integrating computational and experimental workflows Experience supervising or mentoring students Assessment Criteria The position is a career development opportunity focused primarily on research. Assessment is based on: Ability to develop and conduct high-quality research Teaching skills Collaboration and independence in multidisciplinary, scientifically demanding environments Openness to learning new computational and experimental methods Dedication to challenging research projects Demonstrated ability to communicate high-quality research effectively We Offer A unique opportunity to work at the interface of protein design, AI, and semiconductor nanoscience Multidisciplinary and collaborative research environment Access to advanced computational and experimental resources Opportunities for international networking, career development, and independent research ideas Generous benefits, annual leave, and occupational pension schemes as a public authority employee at Lund University Application Instructions Applications must be written in English and include: CV Personal letter explaining interest in the position and match with qualifications Degree certificate or equivalent Optional supporting documents (grade transcripts, letters of recommendation, details of referees) Applications should be submitted via the Lund University application portal. Contact Information: Amijai Saragovi: +46 736 419771, amijai.saragovi@ftf.lth.se Lieselotte Cloetens: +46 462 223853, lieselotte.cloetens@tbiokem.lth.se Jessica Edwinsson: jessica.edwinsson@kilu.lu.se Union representatives: OFR/ST: 046-2229362, st@st.lu.se SACO: kansli@saco-s.lu.se SEKO: 046-2229366, sekocivil@seko.lu.se Published: 07 November 2025 Application deadline: 22 December 2025 If you apply for this position please say you saw it on Bioloxy

Institution: Lunds universitet, Kemiska institutionen, Tillämpad biokemi
Type of employment: Full-time, Temporary (3 years)
Start date: 1 March 2026 or as agreed
Reference number: PA2025/3203
City: Lund
County: Skåne län
Country: Sweden

About Lund University

Founded in 1666, Lund University is consistently ranked among the world’s top universities, with approximately 47,000 students and over 8,800 staff across Lund, Helsingborg, and Malmö. Lund University is committed to gender equality, diversity, and inclusive academic excellence.

Description of the Workplace

The Saragovi Lab at Lund University is part of the Division of Applied Biochemistry within the Department of Chemistry. The lab focuses on combining computational methods, Artificial Intelligence (AI), and high-throughput experimentation to systematically design protein-semiconductor hierarchical materials and de novo hierarchical architectures with atomic precision.

This postdoctoral project aims to design de novo proteins that self-assemble into defined architectures and guide the formation of semiconductor materials with sub-nanometer precision. The position is highly interdisciplinary, involving collaboration between the Departments of Chemistry and Physics, the Center for Molecular Protein Science (CMPS), and semiconductor characterization teams within NanoLund.

The Saragovi Lab offers access to:

Substantial computational resources (GPU nodes)
Advanced high-throughput instruments (FACS, mass photometer, ITC, SPR, etc.)
State-of-the-art characterization tools (high-resolution TEM, ellipsometry, clean-room facilities)

This setup allows a strong computational–experimental feedback loop central to the project.

Subject Description

Recent breakthroughs in deep learning–powered protein design (recognized by the 2024 Nobel Prize in Chemistry) now enable creation of proteins with near-atomic accuracy. Models such as RFdiffusion, LigandMPNN, and hallucination-based frameworks generate symmetric oligomers, cages, and backbones while optimizing sequence properties.

This project focuses on designing proteins that act as templates for inorganic interfaces, forming symmetric oligomers to control inorganic material polymorph, facet composition, and geometry. The goal is to establish a design framework for programmable, functional protein–semiconductor metamaterials, contributing to sustainable biofabrication of (opto-)electronic nanotechnology.

Work Duties

The main duties of the postdoctoral position include conducting research, with teaching limited to a maximum of 20% of working hours. Responsibilities include:

Developing computational protein design pipelines for:
1. Volumes – symmetric or Janus assemblies that encapsulate defined voids
2. Interfaces – templates and catalytic motifs that guide semiconductor formation
3. Pores – structures that regulate selective entry of metal species
4. Inert surfaces – stable outer assemblies in supersaturated solutions
Performing high-throughput expression and screening of designed proteins to evaluate structural and functional quality
Conducting experimental characterization of hybrid soft–hard hierarchical materials
Collaborating with CMPS and NanoLund teams across chemistry, biophysics, and semiconductor science
Contributing to grant applications and external funding acquisition
Handling administrative tasks related to research activities

Qualification Requirements

Applicants must have a PhD (or equivalent international degree) in biochemistry, biophysics, chemistry, computational biology, or a related field. Priority is given to candidates who obtained their PhD within the last three years.

Essential qualifications:

Strong research skills and ability to conduct high-quality research independently
Very good oral and written English proficiency
Solid coding foundation for developing computational protein design pipelines
Basic biochemical laboratory experience
Ability to work independently and collaboratively in a multidisciplinary research environment
Openness to learning and applying new computational and experimental methods
Passion for tackling challenging design problems

Additional qualifications (advantageous but not required):

Extended knowledge of inorganic and organic chemistry
Experience in deep learning model development or computational protein design
Experience integrating computational and experimental workflows
Experience supervising or mentoring students

Assessment Criteria

The position is a career development opportunity focused primarily on research. Assessment is based on:

Ability to develop and conduct high-quality research
Teaching skills
Collaboration and independence in multidisciplinary, scientifically demanding environments
Openness to learning new computational and experimental methods
Dedication to challenging research projects
Demonstrated ability to communicate high-quality research effectively

We Offer

A unique opportunity to work at the interface of protein design, AI, and semiconductor nanoscience
Multidisciplinary and collaborative research environment
Access to advanced computational and experimental resources
Opportunities for international networking, career development, and independent research ideas
Generous benefits, annual leave, and occupational pension schemes as a public authority employee at Lund University

Application Instructions

Applications must be written in English and include:

CV
Personal letter explaining interest in the position and match with qualifications
Degree certificate or equivalent
Optional supporting documents (grade transcripts, letters of recommendation, details of referees)

Applications should be submitted via the Lund University application portal.

Contact Information: