Postdoc (f/m/d) on Generative AI for de Novo Protein Design - 2025/165
Postdoc (f/m/d) on Generative AI for de Novo Protein Design - 2025/165
Postdoc (f/m/d) on Generative AI for de Novo Protein Design - 2025/165
Postdoc (f/m/d) on Generative AI for de Novo Protein Design - 2025/165
Helmholtz-Zentrum Dresden-Rossendorf (HZDR)
Forschung
Görlitz
- Art der Beschäftigung: Teilzeit
- 47.500 € – 55.500 € (von XING geschätzt)
- Vor Ort
- Zu den Ersten gehören
Postdoc (f/m/d) on Generative AI for de Novo Protein Design - 2025/165
Über diesen Job
Ms. Weronika Mazur Tel.: +49 3581 37523 23
Job-Id: 2025/165 (2175)
At HZDR, we promote and value diversity among our employees. We welcome applications from people with diverse backgrounds regardless of gender, ethnic and social origin, belief, disability, age, and sexual orientation. Severely disabled persons are given preference in the event of equal suitability.
Helmholtz-Zentrum
Postdoc (f/m/d) on Generative AI for de Novo Protein Design
With cutting-edge research in the fields of ENERGY, HEALTH and MATTER, around 1,500 employees from more than 70 nations at Helmholtz-Zentrum Dresden-Rossendorf (HZDR) are committed to mastering the great challenges facing society today.
The Center for Advanced Systems Understanding (CASUS) is a German-Polish research center for data-intensive digital systems research.
The Department of Machine Learning for Infection and Disease is looking for a Postdoc (f/m/d) on Generative AI for de Novo Protein Design.
Your tasks
- Design of generative AI models (e.g., VAEs, GANs, Diffusion Models) to create novel protein sequences, fold structures, and functional molecules
- Engage with our international collaborators (Berlin, Dresden, London, Zurich, Taipei etc.) to understand existing approaches and datasets of natural and designed proteins
- Collaborate in the research team on other questions of machine learning, functional genomics, and genome instability
- Supervise junior lab members
- Present results at scientific meetings and publish high-impact peer-reviewed research
Your profile
- Completed university studies (PhD) in a relevant field, such as molecular biology, computational biology, bioinformatics, genetics, computer science, mathematics, or equivalent scientific background
- A solid background and motivation to learn more about structural/molecular biology, protein biophysics, generative models, software engineering, or a related subject
- Previous experience or interest in Generative Modelling, Protein Folding/Design, and Structural Biology is a plus
- Experience with AlphaFold, RFdiffusion, and RFdiffusion2 is a significant plus
- Strong motivation to work in a collaborative multidisciplinary environment
- Excellent programming skills in languages such as Python, C/C++ and CUDA
- Familiarity with modern deep learning frameworks like Tensorflow 2.x.x, PyTorch
- Mandatory experience with High-Performance Computing (HPC) cluster environments and the Slurm cluster environment is required
- Communication skills in English and in a professional context (presentation of research results at scientific meetings, colloquial discussions, writing of manuscripts)
Our offer
- A vibrant research community in an open, diverse and international work environment
- Scientific excellence and extensive professional networking opportunities
- Salary and social benefits in accordance with the collective agreement for the public sector ( TVöD-B und) including 30 days of paid holiday leave, company pension scheme (VBL)
- We support a good work-life balance with the possibility of part-time employment, mobile working and flexible working hours
- Numerous company health management offerings
- Employee discounts with well-known providers via the platform Corporate Benefits
- An employer subsidy for the "Deutschland-Ticket Jobticket"
We look forward to receiving your application documents (including cover letter, CV, diplomas/transcripts, etc.), which you can submit via our online-application-system.
Gehalts-Prognose
Unternehmens-Details
Helmholtz-Zentrum Dresden-Rossendorf (HZDR)
Forschung
