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Field
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PyTorch or TensorFlow, is highly advantageous. Experience in developing and deploying machine learning models, particularly in natural language processing (NLP) and large language models (LLMs), including
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PyTorch or TensorFlow, is highly advantageous. Experience in developing and deploying machine learning models, particularly in natural language processing (NLP) and large language models (LLMs), including
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of the following areas is an advantage: Modelling and simulations of flow in porous media. Programming, image processing and machine learning Personal and relational qualities will be emphasized. Motivation
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investigators in various scientific domains, such as physics, chemistry, and biology, conveying machine learning results and collaborating to explore the insights the models have discovered. - Participated in
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strong, demonstrated interest to conduct academic research in a relevant field Interest in legal research Interest in causal inference and social science Experience with machine learning / deep learning
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for manufacturing operations. Process control: process modelling, control, and optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in
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with machine learning techniques for robotic decision-making and intelligent control for tasks with high uncertainties. Experience with research on multi-agent collaboration and decentralized control
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machine learning Personal and relational qualities will be emphasized. Motivation, ambitions and potential will also count when evaluating the candidates. Special requirements for the position
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AI to predict safety outcomes for multiple targets and combination therapies Collaborate with research teams and data scientists to design data-driven strategies using machine learning/AI methods
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, Machine Learning, Complex Systems Modelling, Space Physics, and Ultrasound, Microwaves, and Optics. The department provides education at the Bachelor, Master, and PhD levels. Contact For further information