67 engineering-computation-"https:"-"https:"-"https:"-"https:"-"UCL" positions at University of Lund in Sweden
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: at least 60 second-cycle credits in subjects of relevance to the subject area, or a MSc in Engineering in Biomedical Engineering, Computer Science, Electrical Engineering, Engineering Mathematics
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biology platform https://www.scilifelab.se/units/structural-proteomics/ The unit provides access to cutting-edge equipment and expertise, for the analysis of protein interactions and conformational dynamics
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Two positions as Associate Senior Lecturer/Assistant Professor in Computational Science (PA2026/927)
for advanced computation with the aim of addressing research problems in the natural sciences, engineering, or medicine. This may include, for example, the integration and development of models, as
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Doctoral student in development of nanowire devices for photonic neuromorphic computing (PA2026/472)
of Engineering, Science, and Medicine. It also operates Lund Nano Lab, a state-of-the-art cleanroom for the synthesis, processing, and characterization of semiconductor nanostructures. Being a doctoral student As a
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, Moving to Lund and Living in Lund . Read more about the University joint announcement: : https://www.lunduniversity.lu.se/lund-university-programme-global-excellence Duties – what we expect from you We
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an umbrella organization and builds on four pillars: Qualitative methods; Experimental methods; Computational Social Science, as well as Skill School (https://www.sam.lu.se/en/research/lund-social
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protection and security, work environment safety and environmental safety at the MAX IV Laboratory. The team is now looking to employ an expert within machine safety. As the sole machine safety engineer, you
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are united in our efforts to understand, explain and improve our world and the human condition. Description of the workplace The Department of Building and Environmental Technology at Lund University comprises
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of Engineering (LTH). Completed FRTF05 Automatic control, basic course with grade 5, or completed FRTN65 Modeling and learning from data with grade 5, or completed FRTF01 Physiological models and computations with
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qualifications: PhD degree in computational science, computational biology, or equivalent Master’s degree in biomedical engineering or equivalent Experience of using various data sources (radiological images