22 experiment-fluid Postdoctoral positions at University of Southern Denmark in Denmark
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research experience at PhD level in a relevant area such as robotics and control preferably applied to robots with flexible links. The candidate is hence expected to have most of the following qualifications
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hands-on experience in tissue handling, histology, microscopy, and spatial transcriptomics. Experience with the computational analysis of NGS- or imaging-based spatial transcriptomics and single-cell
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communication skills and high proficiency in English. Good collaborative and social abilities. Prior experience with animal experimental techniques, transgenic animal work, and standard biochemical techniques
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spectroscopy experiments (electron-energy loss spectroscopy and cathodoluminescence). The project will focus on the description of layered systems combined with individual photonic scatterers or periodic arrays
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experience in artificial intelligence, embedded AI, real-time control systems, or adaptive system architectures. Familiarity with or interest in runtime reconfiguration techniques and system safety
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analyses on harvested tissues and biofluids. The postdoc will be responsible for planning the experiments, data acquisition, preparation, analysis, manuscript writing, and other activities for disseminating
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, robotics, mechatronics, electrical engineering, embedded electronics, or a related subject area. The applicant is expected to have relevant research and teaching experiences that match the position's content
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@mmmi.sdu.dk ). If you experience technical problems with the online application process, contact SDU’s HR support at hcm-support@sdu.dk . Application procedure Applicants are advised to carefully read SDU’s
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, or biomedical engineering (the degree should have been completed within the last 5 years at most) with at least 3 years of experience in designing Artificial Neural Network (ANN) or Spiking Neural
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understanding of chemical safety regulations and frameworks: CLP, REACH, SVHC lists, and GHS classification. Demonstrated experience with: Hazard and risk assessment methods (e.g., QSAR, NAMs, in silico tools