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Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. | Dortmund, Nordrhein Westfalen | Germany | about 11 hours ago
. or Diploma in bioinformatics or a comparable qualification Extensive programming experience Practical experience in machine learning and the application of large language models Knowledge of OMICS and image
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, and machine-learning-based analytics. The research work at NTNU will focus particularly on automation, robotics, mechatronic design, sensor integration, and intelligent experimental systems required
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astrophysics, cosmology, or a related field completed by the start date; strong programming skills; working knowledge of machine learning applied to astrophysics and cosmology, in particular simulation-based
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Engineering, or related field. At least 3 years of relevant experience in computer vision, artificial intelligence, etc. Proficiency in programming languages such as C and Python Proficiency in deep learning
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machine learning. The project combines methodological research in statistics with applications to large-scale social science data. The successful candidates will have the opportunity to collaborate closely
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Join us in developing machine-learning accelerated simulation methods to understand and optimize interfaces in hybrid organic-inorganic materials for sustainable energy devices. Your work
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This PhD asks a different question: instead of demanding more data, can we build language models that learn smarter from less? You will design AI architectures that adapt to the structure of a
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, such as statistical learning, causal inference, experimental design, probability, stochastic PDEs, algebraic statistics, normalizing flows, scientific machine learning, optimization, inverse problems
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or connectivity analysis; machine-learning or deep-learning methods for geospatial analyses; ecological or remote-sensing fieldwork, particularly in alpine environments; Google Earth Engine, geodatabases or cloud
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Eligibility criteria Selection will be based on the following scientific and technical criteria: • PhD in computational biology, machine learning, bioinformatics or a related field. • Proficiency with Python