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Postdoc (f/m/d): Machine Learning for Materials Modeling / Completed university studies (PhD) in ...
Area of research: Scientific / postdoctoral posts Starting date: 01.07.2025 Job description: Postdoc (f/m/d): Machine Learning for Materials Modeling With cutting-edge research in the fields
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theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with
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to develop a 3D-generative algorithm for pharmaceutical drug design by using or combining novel machine learning approaches? How would you integrate machine learning, physics-based methods in an early-stage
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your technical goals. Collaboration opportunities with the Nanoscale Science Department and the European industry leaders in electron microscopy and machine learning, as well as financial support to
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Postdoc (f/m/d) Methods for Geochemical Exploration and Sampling Strategy / Completed PhD in the ...
# Work in an interdisciplinary team to develop analytical and statistical/machine learning methods for surface geochemical exploration # Preparation of multi-method exploration-campaigns for known deposits
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collaborative project between the Ralser lab and the Vingron Lab. This joint endeavor aims to explore phenotype predictions based on large proteomic datasets and machine learning approaches. We are seeking a
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Postdoc (f/m/d) in Machine Learning for Quantum Computing and Simulation of Quantum Matter / Comp...
research (optional) Your profile # Completed university studies (PhD) in the field of Computational Physics or Chemistry, Computer Science with a focus on Artificial Intelligence/Machine Learning methods
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is connected to the vibrant local ecosystem for data science, machine learning and computational biology in Heidelberg (including ELLIS Life Heidelberg and the AI Health Innovation Cluster ). Your
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molecular data Your profile PhD in computer science, mathematics, physics or related fields Experience in machine learning and AI, with proven codebase in public repositories Experience or strong willingness
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or inflammatory processes, e.g., during organ development or tissue regeneration. Your tasks: Bioinformatic, statistical, and machine learning-based analysis of experimental, data generated via a broad spectrum of