15 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at University of Lund
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be made for special reasons). Experience in research on digital cultures. Proficiency in AI methods (e.g., NLP techniques, machine learning, and large language models, LLMs)—including web scraping
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employees and conducts research and teaching mainly in electrical engineering and computer technology. We are located on LTH's campus in northern Lund. At the Division of Electromagnetics and Nanoelectronics
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intelligence for more efficient mathematical and computational approaches. Subject description The work focuses on the design and optimization of various types of turbomachinery. The design and optimization
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will also be involved in data collection by conducting experiments in the fish laboratory. While the focus of the position must be aligned with the group’s scientific vision, the successful applicant
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, e.g., time-series analysis, land use/land cover classification, machine learning methods Experience analysing and visualizing large remote sensing datasets in modern programming language (e.g. R, Python
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at the nanoscale. The Division has a strong commitment to undergraduate education, not least in the Master's programme "Engineering Nanoscience" at LTH. A significant part of the research at our division is in
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. Significant experience of developing deep learning methods using computational frameworks such as PyTorch, TensorFlow etc. Experience of working with molecular questions in the biosciences An interest and
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, teachers, technical/administrative staff, and Ph.D. candidates. The department has a large PhD programme and co-ordinates three international Master programmes. The Department has a well-established
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more efficient use of energy. Approximately 25 colleagues work at the division, including 15 PhD students. On the international level we collaborate with universities and institutes in Europe, Asia, and
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, but up to no more than 20% of working hours. The position shall include the opportunity for three weeks of training in higher education teaching and learning. In general, the candidate will be expected