TU Darmstadt stands for excellent and relevant science. We are playing a decisive role in shaping far-reaching processes of global change-from energy transition to artificial intelligence-through outstanding scientific knowledge and innovative academic programmes. We group our cutting-edge research into three fields: Energy and Environment, Information and Intelligence, Matter and Materials. We are a university with strong ties to the Frankfurt Rhine-Main metropolitan region and a very strong international focus. We are committed to European values and European integration.
The Centre for Synthetic Biology at TU Darmstadt is a university-wide interdisciplinary research initiative bringing together biologists and biochemists with computational scientists and machine learning researchers. The PhD candidate will conduct research in AI method development for the design of novel RNA molecules with application in advanced therapeutic modalities.
In addition, you bring:
On a personal level, you distinguish yourself through:
Your application should include:
The Centre for Synthetic Biology at TU Darmstadt is a university-wide interdisciplinary research initiative bringing together biologists and biochemists with computational scientists and machine learning researchers. The PhD candidate will conduct research in AI method development for the design of novel RNA molecules with application in advanced therapeutic modalities.
PhD in AI-Methods for RNA Design (m/f/d)-E13 (100%)
Activities and responsibilities
- Work on an interdisciplinary topic at the intersection of machine learning / AI and synthetic biology
- Learn the mathematics and algorithms of state-of-the-art RNA language models
- Learn the mathematics and algorithms of state-of-the-art diffusion models for generation of new RNA and protein molecules
- Advance AI methods and models for the design of novel RNA molecules that get conditionally activated upon binding of specific diagnostic RNA molecules
- Find novel ways to Incorporate structure and sequence information in RNA AI-models.
- Build novel AI models for quantitative functional prediction of RNA designs
- Work in close collaboration with experimentalists that conduct high-throughput assays for the characterization of these novel RNA molecules
Qualification profile
- An excellent university science degree (Master’s/Diploma) in computer science, electrical engineering, physics or mathematics. Master’s/Diploma degree must be completed prior to the start of employment.
- Very good programming skills in python; finished larger scientific software projects
- Advanced academic training / background in machine learning and AI methods.
- Experience with dedicated AI methods for molecular design is a big plus.
- Solid understanding of molecular biology and cell biology is a big plus.
- Willingness and drive to work on an interdisciplinary project beyond traditional boundaries.
In addition, you bring:
- Fluency in English for communication in an international team and for writing scientific publications
On a personal level, you distinguish yourself through:
- Analytical thinking and a high degree of self-organization
- Curiosity and creativity
- Openness to working in an interdisciplinary and international team
Your application should include:
- a cover letter explaining succinctly why you want to join this project
- your CV
- bachelor’s and master’s degree certificates and transcript of records
- a list of publications / talks / poster contributions
- contact details of 2 referees
We offer
Technical University of Darmstadt offers varied and challenging assignments, freedom to work independently, the latest technologies, good collaboration between colleagues in partnership, needs-based training opportunities and customised personnel development.
The fulfillment of the duties likewise enables the scientific qualifications of the candidate.
Development and organisation - comprehensive in-house training offers, including the opportunity for continuing education and development;
Annual leave/educational leave - 30 days annual leave (full-time employment) and 5 days educational leave;
Sustainable and mobile - eligibility to free public transport in the state of Hesse with the LandesTicket Hessen (Hesse StateTicket) in accordance with the currently valid collective agreement, in addition to opportunities to working mobile at times;
Fit and healthy - free of charge preventive medical check-ups and a wide-ranging subsidised sports programme;
Work-life balance - flexible working time models, plus BGM (Betriebliches Gesundheitsmanagement - University Health Management);
Pension scheme - supplementary public service pension scheme (VBL) in accordance with the currently applicable regulations;
University bicycle
Family-friendliness/compatibility of family/care/career - (university-run) childcare services, child allowance (based on the collective agreement), childcare programmes during school holidays.
The fulfillment of the duties likewise enables the scientific qualifications of the candidate.
Development and organisation - comprehensive in-house training offers, including the opportunity for continuing education and development;
Annual leave/educational leave - 30 days annual leave (full-time employment) and 5 days educational leave;
Sustainable and mobile - eligibility to free public transport in the state of Hesse with the LandesTicket Hessen (Hesse StateTicket) in accordance with the currently valid collective agreement, in addition to opportunities to working mobile at times;
Fit and healthy - free of charge preventive medical check-ups and a wide-ranging subsidised sports programme;
Work-life balance - flexible working time models, plus BGM (Betriebliches Gesundheitsmanagement - University Health Management);
Pension scheme - supplementary public service pension scheme (VBL) in accordance with the currently applicable regulations;
University bicycle
Family-friendliness/compatibility of family/care/career - (university-run) childcare services, child allowance (based on the collective agreement), childcare programmes during school holidays.
Bitte beziehe dich bei deiner Bewerbung auf jobvector
und verwende die folgende Referenznummer:
AI-RNA-2026
Für diesen Job einen passenden Lebenslauf erstellen und direkt bewerben
Lebenslauf erstellen
