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at the rank of Research Assistant Professor in applied probability, data science, machine learning, and spatial statistics. Candidates with a strong background in the development of novel models and original
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, or a closely related field Strong programming skills, e.g., Python, and familiarity with machine learning and/or software engineering workflows; experience with Git and empirical evaluation Experience
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application to FWO or another external funding organization (depending on your profile and in consultation with your PhD supervisors). Education You will provide support with teaching and also teach high
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tuition assistance and reimbursement Commuter benefits, discounts and campus perks Learn more about these and additional benefits on our Benefits & Wellbeing Page . EEO/Non-Discrimination Commitment
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; May perform routine logging and/or testing of samples; May occasionally instruct others in basic laboratory techniques; Performs related laboratory maintenance such as maintaining and cleaning equipment
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(25260475) Responsibilities: The Department is recruiting a scholar at the rank of Research Assistant Professor in computational mathematics, machine learning, scientific computing, statistics, and related
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Research Assistant Professor, Research Associate Professor, Assistant Professor, Associate Professor
Toxicology and other departments and centers at the Brody School of Medicine and East Carolina University. The tenure-track faculty member will also be expected to teach pharmacology and/or toxicology
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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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related programs (R-language) excitement in learning new concepts and methods joy in conceptual thinking and critical discussion We offer: an interesting research project embedded in the Biodiversity
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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