Research associate (m/f/x) in Data Science in Chemistry (Analytiker/in - Chemie)

In order to fill a fixed-term position in full-time (39.83 hours/week = 100%) at the earliest possible date, we are looking for a

Research associate (m/f/x) in Data Science in Chemistry

At the Chair of Inorganic Chemistry II of the Ruhr University Bochum we address research questions in the fields of organometallic synthesis chemistry and homogeneous catalysis. We are an internationally oriented research team that develops new reagents as well as highly efficient catalysts for synthetic chemistry. By combining advanced synthetic methods, state of the art analytical techniques, quantum chemical calculations, and machine learning methods, we conduct world leading research at the highest international level. Automated analysis of chemical data and the prediction of reactivity, selectivity and yield by means of machine learning are revolutionising modern chemistry. In our group we employ data science methods together with quantum chemical calculations to model reaction networks from experimental data, understand bonding situations and reactivities, and identify new catalysts and reaction conditions in a data driven way.

The Chair of Inorganic Chemistry II (Organometallic Chemistry and Homogeneous Catalysis) is looking for a full time scientific staff member (postdoctoral researcher) (100 % TV L 13) to start immediately. We are looking for a motivated postdoctoral researcher (m/f/x) who, with a passion for interdisciplinary work, will support the design of teaching courses in data science and machine learning and strengthen our group in this area.

Scope: full-time
Duration: fixed-term, 2 Jahre
Start: at the earliest possible date
Apply by: 2026-09-21

Your tasks:

- Quantum‑chemical calculations – perform calculations to elucidate reaction mechanisms, bonding situations and to extract physicochemical properties of molecules
- Model development & validation – create and validate models that clarify structure‑activity relationships and predict properties and reactivities; analyse data with statistical methods and visualise the results
- Collaboration with experimentalists – work closely with laboratory scientists to support and validate data collection
- Project leadership – take responsibility for projects, supervise students, write reports and grant proposals
- Scientific communication – compile results into publications and assist students in preparing manuscripts
- Mentorship – supervise students in their theses and support teaching activities in the areas of Data Science and Machine Learning
- Teaching – support the development and implementation of new student courses in Data Science and Machine Learning

Your profile:

A candidate with a completed university degree and a PhD (preferred) in Chemistry is sought; candidates from related fields such as Data Science or Computer Science with demonstrable knowledge of chemistry are also welcome.

Further requirements:

- Practical experience in quantum‑chemical calculations – familiarity with common quantum‑chemical programs and methods, in particular ORCA, Multiwfn, AIM, etc.
- Practical experience in machine learning & chemistry‑specific data science – programming skills in Python and hands‑on experience with standard libraries such as NumPy, SciPy, pandas, Scikit‑learn, RDKit, PyTorch, etc.
- Practical experience in homogeneous catalysis – desirable, but not mandatory
- Practical experience with the installation and maintenance of high-performance computing clusters – desirable, but not mandatory
- Theoretical knowledge in quantum-chemistry, machine learning, molecular chemistry
- Experience in research project management
- Experience in publishing and presenting scientific results
- Experience in teaching and the supervision of students and interns
- Language skills – English (fluent spoken and written) is required; German is an advantage but not mandatory

Furthermore, the applicant should be open to team‑oriented work and possess a strong motivation for interdisciplinary research.

https://jobs.ruhr-uni-bochum.de/jobposting/c004934036684ad99a5a4bc55ff94c39242c7b740?ref=AfA (https://jobs.ruhr-uni-bochum.de/jobposting/c004934036684ad99a5a4bc55ff94c39242c7b740?ref=AfA)