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Field
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understand, explain and advance society and environment we live in. Your role The University of Luxembourg invites applications for a fully funded Ph.D. position in machine-learning force fields (MLFFs
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. Lead and conduct research projects in data-driven nutrition, such as: statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data
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will develop novel ligands for a validated drug target in acute myeloid leukemia. Building on our promising preliminary results, you will optimize and expand the hit discovery using computer-aided tools
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of visualisation, machine learning, and human-computer interaction under the joint supervision of both institutions. The position is shared by TU Wien and USTP and offers the opportunity to conduct research at both
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, statistics, machine learning) - a high motivation and the ability to work independently with a strong team orientation - excellent spoken and written English and the will to acquire a certain working language
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-good university degree in economics - strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) - a high motivation and the
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or Phonetics Basic knowledge of machine learning tools; familiarity with a scripting language Ability to communicate and coordinate with different partners: field linguists, computer scientists, engineers
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the world. Each of the four campuses (two in Chicago, one in London, and one in Hong Kong) reflects the architectural traditions of its environs while offering a state-of-the-art learning environment. Chicago
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. Strong (inter-)national network in field of application. Experience with high-performance computing (HPC) and large datasets. Experience with machine learning applied to geophysical signals. Experience in
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Networks. Knowledge of and experience in Python, TensorFlow, Keras, or other Machine Learning toolboxes, is essential. Knowledge of and experience in Large Language Models is highly relevant. The successful