Summary
Lund University is offering a fully funded 4-year PhD / Doctoral Studentship position in the Saragovi group at the Center for Molecular Protein Science (CMPS), Department of Chemistry (Kemicentrum). The research project bridges computational protein design, machine learning, and experimental biochemistry to develop programmable protein assemblies that direct the formation of protein–mineral hybrid materials for sustainable (opto)electronic technologies.
Doctoral Student in AI-Based Design of Twisted Hybrid Nanowires at Lund University
Designation
Doctoral Student (PhD Candidate / Doctoral Studentship)
Key Position Details
| Attribute | Details |
| Host Institution | Lund University (Faculty of Science) |
| Department / Lab | Saragovi Group, CMPS, Kemicentrum |
| Position Type | Full-time (100%), Fixed-term employment (4 Years) |
| Salary | Standard Swedish doctoral monthly salary scheme |
| Reference Number | PA2026/2356 |
| Expected Start Date | September 15, 2026 (or by mutual agreement) |
| Location | Lund, Skåne County, Sweden |
| Application Deadline | September 01, 2026 |
Research Area
- Primary Field: Computational Protein Design, Synthetic Biology & Biochemistry
- Specific Topics: Deep learning & reinforcement learning for protein design (e.g., RFdiffusion, ProteinMPNN, AlphaFold), high-throughput protein expression/purification, protein–mineral templating, and biomimetic nanomaterials.
Location
Kemicentrum / CMPS, Lund University, Lund, Skåne County, Sweden.
Eligibility & Qualifications
General & Specific Requirements:
- General Admission: Holds a Master’s (second-cycle) degree, completed at least 240 ECTS credits (with at least 60 in the second cycle), or equivalent.
- Specific Field: Master’s degree (or equivalent) in Molecular Biotechnology, Synthetic Biology, Bioinformatics, Protein Design, Biochemistry, or a closely related field.
Key Skills & Competencies:
- Proven experience with Linux and Python for scientific computing and data analysis.
- Demonstrated experience with state-of-the-art computational protein design platforms (e.g., RFdiffusion, ProteinMPNN, AlphaFold) and reinforcement learning approaches.
- Laboratory experience in molecular biology and protein biochemistry (high-throughput protein expression, purification, and characterization).
- Strong analytical, problem-solving, and communication skills; excellent spoken and written English.
Desirable / Complementary Assets:
- Knowledge of inorganic chemistry, materials chemistry, or biomineralization.
- Experience with materials characterization techniques and scientific publication/grant writing.
Scholarship / Position Description
As a doctoral student in Sweden, you will be formally employed by Lund University with full employee benefits, paid annual leave, social security, and an occupational pension scheme.
- Role & Duties: You will develop generative and reinforcement-learning workflows to design protein assemblies, filter and rank candidates computationally, evaluate them using high-throughput experimental assays (96-/384-well formats, chromatography, spectroscopy), and analyze inorganic hybrid formation.
- Facilities & Compute: Access to advanced laboratory automation, ÄKTA chromatography systems, FACS, SPR, ITC, CD spectroscopy, and a dedicated Linux GPU computing cluster for AI-driven protein modeling.
How to Apply
Applications must be submitted electronically in English through the Lund University Varbi Recruitment Portal.
Required Documents:
- Cover Letter (max 2 pages): Detailing your motivation, passion for research, experience in demanding multi-project workflows, and fit for the Saragovi lab.
- Curriculum Vitae (CV).
- Degree Certificates & Academic Transcripts: Official copies proving general and specific eligibility.
- Supporting Documents: Letters of recommendation or contact information for professional/academic references.
Last Date for Apply
September 01, 2026 (23:59 CET / Swedish Time)







