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the team of Prof. Dr. Loriana Pelizzon on data and methods for supervision of climate and ESG risks in Capital Markets (incl. investment funds, bonds, stocks). The role involves advising and
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for data-efficient exploration and optimization within the process parameter space as well as for adaptive, data-driven machine learning to map the electrolysis process to a digital twin. Data workflows and
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) is an advantage Experience in software tools such as Origin, Matlab, Python/Matplotlib or similar programs for data processing and evaluation. Knowledge of a relevant programming language complements
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mechanisms will be investigated in healthy and clinical populations (i. e. psychiatric or endocrine) both in experimental and cohort data. This highly interdisciplinary research requires a systematic
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summary, a list with 3 or more referees, including contact information. Heidelberg University stands for equal opportunities and diversity. Qualified female candidates are especially invited to apply
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models using experimental data for precise mapping of real processes Conducting detailed analyses of thermomechanical stresses in electrochemical converters using the finite element method (FEM
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in spatial equilibrium modeling (e.g., through coursework, dissertation work, or previous projects) experience with spatial data analysis using GIS tools or spatial libraries and familiarity with
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. Applications from people with severe disabilities are strongly encouraged. For more information about the Max Planck Society and its institutes, please visit: https://www.mpg.de/en/
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for the above-mentioned position from women. Preference will be given to equally-qualified candidates with disabilities. For further information, please contact Prof. Dr. Stefan Schreieder (contact details below
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are looking forward to your application, including a letter of motivation describing your skills and research interest, your CV, and contact information for two references. Please send your application