In the era of big data, harnessing the potential of advanced computational methods such as transformer-based architectures, like Large Language Models (LLMs), has emerged as crucial for an increasingly broad number of domains. We would like to leverage these new architectures for the study of materials and physical systems.

The role will primarily focus on leveraging and adapting transformer-based models to suit the unique challenges presented in materials research, using datasets available at the Helmholtz-Zentrum Hereon.

The position will be at the department of Machine Learning and Data at Hereon’s Institute of Material Systems Modelling.

We are looking for a data scientist, computer scientist, physicist or engineer with a PhD-degree who can start the position as soon as possible. This position is initially limited to 12 months due to funding constraints, with a chance for extension. The place of work is the Helmholtz-Zentrum Hereon in Geesthacht. Part of the work can be conducted via home office.

Equal opportunity is an important part of our personnel policy. We would therefore strongly encourage qualified women to apply for the position. In principle, the full time position (39 h/week) is also sharable.

Your tasks

• pre-processing of the materials datasets for usage by the transformer models
• design and implementation of various transformer-based models
• training and fine-tuning of Large Language Models to test their cross-applicability for engineering and materials science problems
• combination of machine learning architectures with physico-chemical models
• close collaboration with other members of the institute
• publication and presentation of your scientific results in journals and at international conferences and workshops

Your profile

• Your professional profile
• PhD degree in data science, computer science, physics, engineering or related disciplines
• excellent coding skills in Python
• profound knowledge of Python machine learning libraries (e. g., Keras, PyTorch or TensorFlow)
• experience in Artificial Neural Networks
• fluency in spoken and written English
• experience with scientific methods, project planning, publications and presentations
• German language skills are an advantage

Your personal profile

• systematic and goal-oriented way of working
• sense of responsibility and a high demand for quality in your work
• ability to tackle complex problems and to think outside the box
• joy of working in a small team and flexibility regarding the tasks involved
• proactive communication skills
• openness to an international and dynamic working environment in science
• willingness to familiarize yourself with new topics, e. g. physics of the datasets you are using for testing the ML algorithms

We offer you

• an exciting and varied job in a research centre with more than 1,000 employees from around 60 nations
• a well connected research campus and best networking opportunities
• individual opportunities for further training
• social benefits according to the collective agreement of the public service and remuneration
• an excellent technical infrastructure and modern workplace equipment
• 6 weeks holiday per year; company holidays between Christmas and New Year's Day
• very good compatibility of private and professional life through offers of mobile and flexible work
• family-friendly company policy with childcare facilities, e. g. nursery close to the company
• free assistance program for employees (EAP)
• Corporate Benefits
• a varied offer in the canteen on campus