Senior Scientist - Research Group Lead (m/f/d)

Senior Scientist Postdoc / Research Group Lead (m/f/d)

Institute: Smart Reactors

Remuneration: EG 14 TV-L

ID: 38525WV4

Start of employment: 1 April 2026

Application deadline: 25 January 2026

Scope: Full time, fixed-term for three years (after successful assessment extension for another three years possible)

Scope

The Collaborative Research Center (CRC) 1615 "SMART Reactors for Future Process Engineering" aims to develop reactors that autonomously and sustainably convert renewable feedstocks into a wide variety of products. To contribute to this vision, we are establishing a Junior Research Group dedicated to machine learning (ML), automation, and multiscale modeling, focusing on material and process development. This group will aid the CRC 1615 with state‑of‑the‑art ML tools tailored to the diverse needs of experimental and simulation‑based subprojects. Anchored at the Institute of Process Systems Engineering, the group will collaborate closely with application‑driven PIs from across the CRC. By identifying structurally similar problems and cross‑cutting use cases, the group will transfer developed methods and insights throughout the center.

Your Tasks

• Development and adaptation of cutting‑edge machine learning methods tailored to CRC 1615 use cases
• Coordination of collaborative research activities and scientific integration across CRC subprojects
• Scientific guidance of PhD students within the group
• Development of teaching materials and establishment of a new course in Scientific Computing and Machine Learning in Chemical Engineering
• Preparation of high‑quality scientific publications and presentations

Your Profile

• University degree in the subject of Computational Engineering, Computer Science, Data Science, Chemical Engineering, or a closely related field, doctorate

Required Knowledge And Personal Skills

• Strong publication record and proven research experience in multi‑scale modeling and machine learning techniques to chemical engineering challenges
• In‑depth expertise in model identification, applying e.g. approaches such as symbolic regression and neural networks
• Experience in applied process optimization, for materials and process development e.g. Bayesian Optimization and active learning
• Excellent communication and collaboration skills; demonstrated ability to work independently and lead research activities or teams

Our Offer

• The opportunity to pursue further academic qualification (e.g., habilitation)
• Close integration with a DFG‑funded research center working and connection to the research initiative Machine Learning in Engineering (MLE)
• Participation in national and international conferences, including options for research stays abroad
• A job in an interesting, friendly, supportive and appreciative working environment
• Intensive induction and onboarding
• 30 day vacation per year

Contact

For further information please contact Prof. Mirko Skiborowski, Tel.-Nr. , email:

Equal Opportunity Statement

We value diversity, therefore all applications are welcome, regardless of gender, gender identity, ethnic origin, nationality, age, religion and belief, disability, sexual orientation and identity or social background. The TUHH stands for equal opportunities as well as appreciative and respectful cooperation.