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of algorithms, machine learning, optimization, scientific software development and high-performance computing. The division is also an important part of the eSSENCE strategic collaboration on e-science and of
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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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systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization
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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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, spans the breadth of computing disciplines. Our internationally visible research, strong industry links and diverse environment create a collaborative setting where ideas grow into real impact. At
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collaboration with experimental LNP PhD / PostDoc projects in the Barriga Lab and with M. Carroni at the Cryo EM facility SciLifeLab. Other responsibilities may include teaching, supervision and contributions
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Sweden through collaboration within supported projects, consultations, mentoring, and advanced national postgraduate courses. Engage in the strategic development of advanced machine learning and AI
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computational methods with a particular focus on deep learning and image analysis. The project relies on a close collaboration with researchers at the Department of Immunology, Genetics and Pathology (IGP
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research across various areas, managed under the Department of Immunotechnology. Through the collaborative project L2Bridge, which is supported during five years by a donation (https://www.lu.se/artikel
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and hardware design, and biophysical modeling. We do not expect applicants to arrive with expertise in all of these. What matters most is a demonstrated ability to learn new methods, a willingness to