Doctoral student in AI based design of twisted hybrid nanowires Full-time

Doctoral Student In Ai Based Design Of Twisted Hybrid Nanowires

Lund University was founded in 1666 and is repeatedly ranked among the world's top universities. The University has around 46 000 students and 8 500 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition.

The position is based in the Saragovi group at CMPS, Kemicentrum, Lund University. The group's research focuses on the design of proteins that can template and direct the formation of protein–mineral hybrid materials for next-generation sustainable (opto)electronic technologies. By combining computational protein design with experimental biochemistry and materials characterization, we seek to develop biologically inspired approaches for fabricating functional materials with precisely controlled properties. The group is currently composed of several master's-level research assistants and is in the process of recruiting multiple PhD students and postdoctoral researchers. This is an exciting opportunity to join the laboratory at an early stage and contribute to shaping its scientific direction, culture, and future growth. Team members work closely together across computational and experimental disciplines, providing opportunities to develop a broad range of expertise while working on ambitious interdisciplinary research projects.

We are committed to translating fundamental discoveries into technologies with real-world impact. The lab first spinout company is already funded and operational, with additional translational opportunities under development. This provides a unique environment for researchers interested in pursuing future careers in either academia targeting hard basic research problems or technology development and entrepreneurship. We value community spirit, dedication, and the pursuit of innovative science with the potential to make a meaningful impact on sustainability and future technologies.

As a doctoral student, you are both admitted as a student and employed at Lund University. As a doctoral student, you will be trained in a scientific approach. In short, you will be trained to think critically and analytically, to solve problems independently using the right methods, and to develop an awareness of research ethics. In addition, you will have the opportunity to work on projects, to develop your leadership and pedagogical skills. Throughout your studies, you will be guided by supervisors. Doctoral studies end with a thesis and a doctoral degree.

The doctoral project focuses on the computational and experimental design of proteins that self-assemble into architectures containing precisely defined geometric voids capable of directing mineral growth. These protein assemblies will serve as programmable templates for the formation of protein–mineral hybrid materials with applications in next-generation sustainable (opto)electronic technologies. The project combines computational protein design with experimental validation. On the computational side, the doctoral student will apply and further develop state-of-the-art deep learning and reinforcement learning approaches for protein design. On the experimental side, the work includes application of high-throughput biochemical and biophysical assays to exprerss, validate and functionally evaluate the designed proteins and the resulting hybrid materials.

The work duties include:

• Develop reinforcement learning-based protein design workflows, building on state-of-the-art methods from the scientific literature, to generate two-component protein assemblies with grafted functional motifs.
• Develop novel computational methods to filter, rank, and prioritize designs
• Apply state-of-the-art sequence design and structure prediction models as an evaluation (“oracle”) step to assess, refine, and prioritize computational designs before experimental validation.
• Utilize high-throughput 96- and 384-well and library bassed protein expression, purification, and characterization workflows to rapidly evaluate designed protein assemblies.
• Develop and perform functional assays to identify protein assemblies that direct the formation of inorganic materials and meet the project's design objectives.
• Continuously review the scientific literature and develop into an international expert in your research area, including protein design methods, computational tools, and materials systems.
• Initiate and lead complementary research projects that strengthen and expand the overall objectives of the research programme.
• Collaborate closely with other members of the laboratory by sharing knowledge, supporting your colleagues, and contributing to an open, collaborative, and positive research environment.
• Present your research at group meetings, national and international conferences, and through publications in leading scientific journals.
• The duties may also include participation in teaching and other departmental work (however, a maximum of 20% of working hours).

To be eligible for admission and employment as a doctoral student, you must fulfil the requirements below.

A person meets the general admission requirements for third-cycle courses and study programmes if the applicant:

• Has been awarded a second-cycle qualification, or
• Has satisfied the requirements for courses comprising at least 240 credits of which at least 60 credits were awarded in the second cycle, or
• Has acquired substantially equivalent knowledge in some other way in Sweden or abroad.

A person meets the specific admission requirements for third cycle studies in Biochemistry and Structural Biology if the applicant has:

A Master's degree, or equivalent qualification, in Molecular Biotechnology, Synthetic Biology, Bioinformatics, Protein Design, Molecular Biotechnology, or another closely related field relevant to the research project.

In order to complete the doctoral programme in question, the following are also required:

• Proven experience working in developing Linux AND Python-based computational workflows for advanced scientific data analysis and computational research.
• Knowledge and experience in developing and applying state-of-the-art computational protein design platforms, including backbone generation models (e.g. RFdiffusion), reinforcement learning approaches, protein sequence design models (e.g. ProteinMPNN), and structure prediction models (e.g. AlphaFold or similar).
• Experience with molecular biology and protein biochemistry, particularly the development and utilization of high-throughput experimental workflows for protein expression, purification, and functional characterization.
• Excellent analytical, problem-solving, and organizational skills, with the ability to work independently, manage multiple research projects simultaneously, and demonstrate the work ethic and resilience required to thrive in a highly demanding research environment.
• Excellent collaboration and communication skills, with the ability to contribute to a positive and supportive research environment.
• Good written and oral communication skills
• Very good knowledge of English, spoken and written

For the doctoral programme in question, the following are considered as other qualifications:

• Knowledge of inorganic chemistry, materials chemistry, or mineralization processes.
• Experience with inorganic materials characterization techniques
• Experience with scientific writing, including manuscripts, research proposals or grant applications, posters, and oral presentations.
• Experience working in interdisciplinary research environments spanning computational biology, protein engineering, and materials science.

Lund University is a public authority which means that employees get particular benefits, generous annual leave and an advantageous occupational pension scheme. Our facilities include advanced instrumentation for protein production, purification, and characterization, including ÄKTA chromatography systems with size-exclusion chromatography (SEC), 96-well autosamplers and fraction collectors, benchtop flow cytometry and cell sorting (FACS), glove boxes for air-sensitive experiments, surface plasmon resonance (SPR), isothermal titration calorimetry (ITC), advanced circular dichroism (CD) spectroscopy, bioreactors, incubators, shakers, and high-throughput laboratory automation. You will also have access to a dedicated Linux-based GPU computing cluster for AI-driven protein design and machine learning, enabling the development and application of state-of-the-art computational methods alongside experimental validation.

The employment is a fixed-term employment at full time, starting 2026-09-15 or as agreed. Third cycle studies consist of full-time studies for 4 years. In the case of teaching and other departmental duties, the employment is extended accordingly. Doctoral studentships are regulated in the Higher Education Ordinance (1993:100), chapter 5, 1-7 §§.

Please provide a cover letter (maximum two pages) describing:

• Your motivation for applying for the position.
• Your passion for scientific research and commitment to excellence.
• Your approach to working in a highly demanding, fast-paced research environment involving multiple concurrent projects.
• Why you believe you are a good fit for the position and our research group.

Interviews will be conducted online.

Applications shall be written in English and include:

• CV and a cover letter stating the reasons why you are interested in the doctoral programme/employment and in what way the research project corresponds to your interests and educational background.
• Copies of issued study certificates and/or awarded degree certificates. These must confirm that you meet the general and specific admission requirements for the doctoral programme and show that you have the subject knowledge required for the doctoral programme project.
• Other documents you wish to be considered (grade transcripts, contact information for your references