PhD position Untangling multi-property NMR signals in drug screening with data-driven neural networks Karlsruher Institut für Technologie (KIT)
Temporary
Part Time
Apply by: 2026-07-23
Published: 2026-06-25
Eggenstein-Leopoldshafen
Karlsruhe Institute of Technology (KIT) – The University in the Helmholtz Association
In close partnership with society, KIT develops solutions for urgent challenges – from climate change, energy transition and sustainable use of natural resources to artificial intelligence, sovereignty and an aging population. As The University in the Helmholtz Association, KIT unites scientific excellence from insight to application-driven research under one roof – and is thus in a unique position to drive this transformation. As a University of Excellence, KIT offers its more than 10,000 employees and 22,800 students outstanding opportunities to shape a sustainable and resilient future.
KIT – Science for Impact.
The Scientific Computing Center (SCC) is the Information Technology Center of KIT.
The junior research group “Robust and Efficient AI” at SCC conducts research on scalable AI methods for applications in the natural sciences. The team focuses particularly on the question of how machine learning can be made more robust and efficient to enable the use of such methods in complex and safety-critical application areas.
Since many of these applications rely on extremely large datasets, high-performance computing (HPC) plays a central role in the group's research.
Curious about an exciting and versatile role in an agile team? Discover more about SCC as your professional place to be: https://www.scc.kit.edu/en/aboutus/working-at-scc.php
Scientific Computing Center (SCC)
2030-06-30
asap
Part-time
43,200.00 to 46,400.00 EUR gross per year
In close partnership with society, KIT develops solutions for urgent challenges – from climate change, energy transition and sustainable use of natural resources to artificial intelligence, sovereignty and an aging population. As The University in the Helmholtz Association, KIT unites scientific excellence from insight to application-driven research under one roof – and is thus in a unique position to drive this transformation. As a University of Excellence, KIT offers its more than 10,000 employees and 22,800 students outstanding opportunities to shape a sustainable and resilient future.
KIT – Science for Impact.
The Scientific Computing Center (SCC) is the Information Technology Center of KIT.
The junior research group “Robust and Efficient AI” at SCC conducts research on scalable AI methods for applications in the natural sciences. The team focuses particularly on the question of how machine learning can be made more robust and efficient to enable the use of such methods in complex and safety-critical application areas.
Since many of these applications rely on extremely large datasets, high-performance computing (HPC) plays a central role in the group's research.
Curious about an exciting and versatile role in an agile team? Discover more about SCC as your professional place to be: https://www.scc.kit.edu/en/aboutus/working-at-scc.php
PhD position Untangling multi-property NMR signals in drug screening with data-driven neural networks
Your Tasks
Within the Collaborative Research Center (SFB) HyPERiON at KIT, an innovative PhD project is offered that focuses on resolving signal overlap in parallel NMR spectroscopy using artificial intelligence (AI). NMR spectroscopy is a key tool in drug discovery. However, in a parallel setup, signal couplings and overlaps occur that make it difficult to extract critical molecular information. The aim of the project is to develop AI models capable of generating individual, decoupled spectra from coupled NMR spectra.Within the scope of the project, your responsibilities will include:
- Developing a transformer-based neural network for the processing of NMR spectra
- Creating datasets from existing experiments within the CRC and from your own experiments, which are to be carried out during a research stay at KIT's Institute of Microstructure Technology (IMT)
- Applying self-supervised pretraining based on masked sequence modeling and task-specific fine-tuning to the trained neural network
- Analyzing the extent to which the developed model can learn the underlying physical principles of nuclear magnetic resonance
Key Focus Areas
- Scalable deep learning methods for nuclear magnetic resonance
- Self-supervised pre-training techniques and transfer learning approaches in Transformer-based architectures
- GPU-based computing and high-performance computing (HPC)
- Application of AI methods in a scientific context
Your Profile
Job requirements:- M.Sc. in computer science, physics, mathematics or equivalent discipline
- Very good programming and software development skills, preferably in Python
- Prior experience with deep learning model development and training, or nuclear magnetic resonance methods
We Offer
Science for Impact
Engage with topics of societal relevance — in an excellent scientific environment that enables change.
Flexible Working Hours
Take advantage of flexible hours schemes, remote work options, part time models, and a 30 day annual leave entitlement to achieve an optimal work life balance.
Individualised Extra Benefits
Enjoy a corporate pension (VBL), a €25 monthly contribution toward a JobTicket BW, plus a broad selection of cultural and recreational programmes.
Family-friendliness
The “KIT Family +” program assists you in reconciling work and family life by offering childcare services, holiday activities, a parent child office space, and assistance with caring for relatives.
Stay Healthy
Under the motto “Fit at KIT – Body, Mind and Soul,” we promote your well being through fitness classes, mental health programmes, and regular preventive health examinations.
Career-Building and Developmental Opportunities
We provide you with a structured onboarding program, a broad spectrum of continuing education options, and personalised support, thereby fostering your individual growth.
Salary
Salary category 13 TV-L; classification is based on personal and professional qualifications.
Job location
Eggenstein-Leopoldshafen (and Karlsruhe)
Contract duration
2030-06-30
Contact person in line-management
Frau Dr. Charlotte Debus
charlotte.debus@kit.edu
If you have general questions about the application process, please contact
Dominik Meschar
Personalservice (PSE)
dominik.meschar@kit.edu
+49 721 608-25029
At KIT we value the diversity of our employees; different perspectives and backgrounds enrich our work. We therefore welcome applications from all candidates. Women are especially encouraged to apply. Applications from recognized severely disabled individuals are given preferential consideration when qualifications are equal.
Application up to: 2026-07-23
Job posting number: 282/2026
KIT processes your personal data in accordance with this Privacy Policy.
Salary category 13 TV-L; classification is based on personal and professional qualifications.
Job location
Eggenstein-Leopoldshafen (and Karlsruhe)
Contract duration
2030-06-30
Contact person in line-management
Frau Dr. Charlotte Debus
charlotte.debus@kit.edu
If you have general questions about the application process, please contact
Dominik Meschar
Personalservice (PSE)
dominik.meschar@kit.edu
+49 721 608-25029
At KIT we value the diversity of our employees; different perspectives and backgrounds enrich our work. We therefore welcome applications from all candidates. Women are especially encouraged to apply. Applications from recognized severely disabled individuals are given preferential consideration when qualifications are equal.
Application up to: 2026-07-23
Job posting number: 282/2026
KIT processes your personal data in accordance with this Privacy Policy.
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