24 parallel-programming PhD scholarships at Chalmers University of Technology in sweden
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We are offering a WASP, The Wallenberg AI, Autonomous Systems and Software Program, funded PhD position that provides a unique opportunity to develop deep expertise in robotics, machine learning
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implementation. About the project Reactive synthesis refers to the automatic generation of programs from high-level behavioral specifications. This approach plays an increasingly important role in areas such as
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artificial intelligence is transforming human culture and collective memory. The Wallenberg AI, Autonomous Systems and Software Program – Humanity and Society (WASP-HS) is a national research program in
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competitive performance. This position is supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP). WASP is Sweden’s largest individual research program ever, a major national initiative
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sustainable future through materials science. All early-stage researchers recruited into the WISE programme will be a part of the WISE Research School , an ambitious nationwide programme of seminars, courses
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analysis using AI. Solid knowledge of signal processing and machine learning. Proficiency in programming (e.g., MATLAB, Python, C/C++). Strong written and verbal communication skills in English. The
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%) Complete coursework relevant to the PhD program Your profile Required qualifications MSc degree in Environmental Engineering, Chemical Engineering, Civil Engineering, Biotechnology, or a related field
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aluminium. The candidate will investigate various methods for symbolic regression, aiming to extract symbolic information, like mathematical functions or programs from a network trained for material modelling
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into the WISE programme will be a part of the WISE Research School Who we are looking for The following requirements are mandatory: To qualify as a PhD student, you must have a Master's degree (masterexamen) of
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qualifications Documented experience with data analysis and programming (e.g., Matlab, Python or R). Experience of risk assessment and/or decision analysis Experience of probabilistic methods such as Monte Carlo