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

PhD position Untangling multi-property NMR signals in drug screening with data-driven neural networks

75% part-time

Scientific Computing Center (SCC)
2030-06-30
asap
Part-time
43,200.00 to 46,400.00 EUR gross per year

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

You will further be part of HyPERiON, participating in CRC activities and engage with the other PhD students and projects.

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

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

Science for Impact
Engage with topics of societal relevance - in an excellent scientific environment that enables change.

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.

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.

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.

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.

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.

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Karlsruher Institut für Technologie (KIT) Campus Nord

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Job Overview

Verfügbar ab

29.06.2026
Besucher

1,560 Besuche
Anzahl

1 Freie Stelle
Verfügbar bis

29.09.2026
Arbeitsort

76344 Eggenstein Leopoldshafen
Schulbildung

Branchenspezifisch
Kategorie

Sonstige

Kontakt Info

76344 Eggenstein Leopoldshafen