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PhD position (f/m/d) on „Data-guided experimentation and machine learning“
Compositionally complex solid solutions, also referred to as high entropy alloys, show promise for clean energy systems. Their unique properties arise from complex surface structures, opening doors to better electrocatalysts. Our research focuses on understanding and controlling these surface structures, paving the way for more efficient and sustainable materials. The interdisciplinary approach involves experts in materials science, surface science, physics, chemistry, and data science. The goal is not just to create new catalysts but to enhance our fundamental understanding, eventually leading to the design of versatile and efficient electrocatalysts using abundant materials.
Within this CRC, the tasks associated with the position include the development and implementation of data fusion from various experimental and simulation data sources at different length scales characterizing different properties of surfaces. Following that, the development and implementation of Active Learning to guide the design of compositionally complex solid solutions as catalysts. You will closely interact with the data infrastructure project and the project for the development of a knowledge graph for compositionally complex solid solutions. Through the former collaboration, you will receive the data from all other groups, the latter collaboration ensures that the knowledge created from the data is usable.
Your tasks:
- Data fusion and feature engineering for data from simulation and experimental groups; data comprises:
-Synthesis parameters
-Surface characterization
-Electrocatalytic characterization
-Theory-based predictions - Implementation of an Active Learning framework using Bayesian Optimization to guide experiments
- Derivation of design rules for compositionally complex solid solutions applied to catalysis based on concepts from explainable artificial intelligence.
Your profile:
We seek an outstanding science-driven candidate with strong programming abilities and a background (Master’s degree or equivalent) in Materials Science, Physics, Chemistry and/or Computer Science. One requirement is proficiency with the programming language Python. Experience with typical Machine Learning libraries (scikit-learn, scikit-image, tensorflow, pytorch, etc.) and management of scientific data is beneficial.
The position:
- temporary until 31.12.2027
- full time: 39,83 hours per week
- TVL E13
- start: as soon as possible
Our offerings:
- Team-orientated cooperation in a committed, international and appreciative team a friendly and collegial environment
- Options for flexible working within Germany
- Extensive training and further education opportunities
- a job in the centre of the lively Ruhr metropolitan region with its diverse cultural offerings
Additional information:
At the request of the applicant (m,f,x), the staff council may be involved in selection interviews. https://www.wpr.ruhr-uni-bochum.de/
If the position is funded by third-party funds the employee has no teaching obligation.
German language courses are offered by the University Language Center (ZfA) in the field of German as a Foreign Language (DaF). https://www.daf.ruhr-uni-bochum.de/sbgk/index.html.en
The Ruhr-Universität Bochum is one of Germany’s leading research universities, addressing the whole range of academic disciplines. A highly dynamic setting enables researchers and students to work across the traditional boundaries of academic subjects and faculties. To create knowledge networks within and beyond the university is RUB’s declared aim.
The Ruhr-Universität Bochum stands for diversity and equal opportunities. For this reason, we favour a working environment composed of heterogeneous teams, and seek to promote the careers of individuals who are underrepresented in our respective professional areas. The Ruhr-Universität Bochum expressly requests job applications from women. In areas in which they are underrepresented they will be given preference in the case of equivalent qualifications with male candidates. Applications from individuals with disabilities are most welcome.
Contact details for your application:
Markus Stricker, Phone: +49234 32 23977
Application deadline is 26.02.2024
Travel expenses for interviews cannot be refunded.
For information on the collection of personal data in the application process see: https://www.ruhr-uni-bochum.de/en/information-collection-personal-data-application-process.
ANR: 2871 until 26.02.2024, Please send your complete and informative application documents (cover letter, 1-page motivational letter, CV with certificates) as one PDF document by e-mail to Jun.-Prof. Dr.-Ing. Markus Stricker markus.stricker@rub.de
The Ruhr-Universität Bochum is one of Germany’s leading research universities, addressing the whole range of academic disciplines. A highly dynamic setting enables researchers and students to work across the traditional boundaries of academic subjects and faculties. To create knowledge networks within and beyond the university is RUB’s declared aim.
The Ruhr-Universität Bochum stands for diversity and equal opportunities. For this reason, we favour a working environment composed of heterogeneous teams, and seek to promote the careers of individuals who are underrepresented in our respective professional areas. The Ruhr-Universität Bochum expressly requests job applications from women. In areas in which they are underrepresented they will be given preference in the case of equivalent qualifications with male candidates. Applications from individuals with disabilities are most welcome.