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the Institute of Advanced Simulation – Materials Data Science and Informatics (IAS-9) and the Institute of Energy Materials and Devices – Structure and Function of Materials (IMD-1) to establish a data-driven
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environment. For more information about the Program for Collaborative Doctoral Projects, please visit: https://go.fzj.de/Collaborative-Doctoral-Projects . We are offering an interesting Collaborative Doctoral
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. Strong coding skills for programming neural networks, machine learning and machine learning software frameworks (e.g. PyTorch or Jax) is a must. The ability for creative and analytical thinking across
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such as the NEPS. Potential research areas include (but are not limited to): Item response modeling of achievement tests Analysis of process data (e.g., response times) to enhance competence measurements
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well as analytical methods are an advantage Willingness to handle unsealed radioactive materials within a radiation-controlled laboratory environment Knowledge of handling radioactive materials and radiochemical
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a focus in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation
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. Qualifications The applicants should possess: An excellent or very-good university degree in economics, business studies, agricultural sciences with a focus in economics, or related disciplines Strong analytical
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PhD Position - Organic Electrosynthesis: monitoring of reaction transients with real-time techniques
for selected electro-organic transformation in detail: Design, validation and verification of online and offline analytical methods Design, synthesis, and characterization of catalytic materials Utilization
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disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with
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analysis and analytical data analysis workflows, together with other team members Implementing AI-based microscopy image analysis software as python packages Developing algorithms to deploy machine learning