97 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "Univ" "Univ" positions at University of Lund in Sweden
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very good ability in evaluating and presenting data. Ability to work in a structured and autonomous way. The ability to independently plan, perform and evaluate research studies. Very good oral and
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Information Technology conducts broad research in cryptography, computer security, wireless and wired networks. The Security Group has around 20 members. The main research areas are cryptography, privacy, and
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Therapy (MMGT) at the Biomedical Centre (BMC). MMGT houses labs with a variety of complementary expertise in stem cell biology and gene editing. More information on the lab can be found at leighnd.github.io
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the beamline. Main work tasks As part of the team, you will actively help maintain and run the beamline, the end-stations and data processing tools, with a primary focus on magnetic experiments and/or coherent
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engines (e.g. Unity, Unreal or Godot) and programming skills (e.g. Java, or C#). knowledge related to the analysis of physiological data. knowledge in the area of game development. previous thesis work
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project follow-ups. More information about MoRe‑Lab and our activities is available on our website . We offer Lund University is a public authority which means that employees get particular benefits
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has aimed to develop a two-part research programme. The first part focuses on developing and applying methods for 3D digital modelling, ranging from the collection of digital data from archaeological
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prototype rigs, as well as circuit boards experience in using 3D printing systems experience from being responsible for computer networks or maintaining/updating software for computer-based control systems
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to terawatt lasers at the High-Power Laser Laboratory. The research areas include the interaction between intense laser fields and matter, attosecond science, quantum information, solid-state X-ray
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at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model reduction, with