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and/or pump-probe techniques. Strong optics experience including building and/or adapting setups is essential, and experience working with coding, automation and algorithm development highly desired
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methods to improve the deployment, adaptation capabilities and safety of robots and critical infrastructures. The developed algorithms will be evaluated on legged robots, wheel-based robots and under
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modelling, advanced AI algorithms, and decision-support tool development for various hydrogen technologies-based energy systems. Responsibilities will include programming, analysing and interpreting data, and
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image acquisition capabilities. Together, we are developing next-generation Ai-assisted robots for colorectal cancer treatment. About The Role EndoTheranostics aims to transform the screening and
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in our team. Learn more about us here: https://sc.cs.univie.ac.at/ Your future tasks: Active participation in research, teaching and administration, which means: You develop your independent research
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application. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development for various hydrogen technologies-based energy
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About Us We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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the UK PI Dr Richard Brown (Durham) and Co-I Prof Paul Brennan (UCL), Co-I Prof Patrice Carbonneau (Durham), and Co-I Dr Silvio de Angelis, and Prof Jim McElwaine (Woods Hole, USA). The project involves
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transport for inverse problems One of the central topics of the research projects is the further development of theory and methods for the concept of optimal transport for inverse problems. Optimal transport
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of Oxford. The post is funded by the National Institute for Health and Care Research (NIHR) and is fixed term for 24 months. The researcher will develop multi-sensor 3D reconstruction algorithms to fuse