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one or more of the following areas is meriting: Bayesian statistics, mathematical modelling, probabilistic machine learning, deep learning, large language models. Rules governing PhD students are set
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machine learning for the next generation of AI models – uncertainty-aware foundation models, generative models and world models – with the support of competent and friendly colleagues in an international
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earlier. The three-year period can be extended due to circumstances such as sick leave, parental leave, duties in labour unions, etc. Documented experience in machine learning, in particular deep generative
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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higher education credits (ECTS). Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural networks, as well as courses in Python, GPU programming
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Bioinformaticians in advanced Machine Learning and AI The Department of Biochemistry and Biophysics. SciLifeLab (SciLifeLab ) is a national center for molecular biosciences with focus on health and
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modeling of protein dynamics We are seeking a highly motivated PhD student to join a DDLS-funded project at the interface of structural proteomics, protein biophysics, and machine learning. The position is
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) to help shape and accelerate the adoption of advanced machine learning and AI in data-driven Life Science research. At the SciLifeLab Bioinformatics Platform (NBIS), a unique national infrastructure with
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a doctoral student with a strong background in machine learning, mathematics, and modeling, and an interest in biological systems. The successful candidate will join a project to understand and model
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measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with modern deep learning frameworks (PyTorch, JAX, or equivalent). Have