48 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" uni jobs at University of Southern Denmark
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Computer Science, a BSc degree in Artificial Intelligence, and an MSc degree in Data Science. More information about the department can be found at https://imada.sdu.dk/ . The University of Southern Denmark (SDU
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Applicants should have strong experience in one or more of the following overlapping areas: Analog and mixed-signal IC design: amplifiers, references, data converters, sensor interfaces, and power management
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activities in the SDU Robotics project activities. For a research project in the field of lab automation we are looking for a student assistant: Robotic and mechanical focused: Helping with data analysis and
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the professorship. Contact information Coordinative Head of research, Esbjerg University Hospital/University of Southern Denmark, Torben Knudsen; torben.knudsen@rsyd.dk/ +45 21627219. Head of the Department
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. The degrees offered by the department include BSc, MSc, and PhD degrees in Mathematics, Computer Science, Data Science and specializations in STEM Education. More information about the department can be found
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, biomaterials, circular design practices or other related developments. Proven experience with data-driven methods will be regarded as advantageous. Experience in developing and managing laboratory infrastructure
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communication skills for reporting and documenting flight operations For further information about the position and the application procedure, please contact Alin Drimus, Associate Professor tel. 6550 1689, e
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, and Maintenance Software Reliability Engineering Systems Engineering Model-Driven Engineering Modeling, Simulation and Data Analytics Human-Computer Interaction and Design Interactive Systems
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robotic system capable of autonomously performing standard echocardiography. Your primary tasks will include: Setup annotation platform for labelling Echocardiography videos. Supporting data collection and
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on in vivo release of LAI suspensions in nonclinical models using the obtained data to generate a risk matrix for in vivo impact of potential particle size variations. A successful outcome of this