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Field
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robotics, embodied AI and neurobotics, wearable robotics, and bio-inspired control. SDU Soft Robotics is a leading research group within SDU Biorobotics. We design, build, and program next-generation bio
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information sciences. In parallel with basic research, we develop ideas and technologies further into innovations and services. We are experts in systems science; we develop integrated solutions from care
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, cyber-physical systems, real-time systems, autonomous systems, middleware, parallel computing, operating systems, Edge AI or AI in cyber-physical systems; Demonstrate strong analytical, programming, and
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Your tasks: Developing optimization algorithms for massively parallel hardware architectures such as AI
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Mar 2026 - 22:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 40.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU
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Network with 15 funded 3-year PhD positions in parallel. Your profile Master Degree in environmental/natural sciences or engineering, or similar. Experience with developing computational models Preferably
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-phase chemistry coupled with solid-phase reaction clean up using tethered reagents that enable pure compounds to be screened without further purification. These methods will allow the parallel synthesis
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screened without further cumbersome purification. These methods will allow the parallel synthesis and testing of ca. 100 compounds in a single operation, potentially taking less than a week to design
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Declaration of interest regarding PhD project within the field of biomarker and therapeutic targe...
. The PhD student will work with patient cohort to perform biomarker analyses and statistical modeling of clinical outcomes. In parallel, the student will contribute to the development and validation of novel
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through sensitivity, uncertainty, and scalability analyses. – Enhance the computational efficiency of large-scale optimization problems by exploring decomposition techniques, parallelization, and