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future autonomous instrument control and self-directed experimentation will be developed, recognizing the challenge presented by the integration of multiple complex systems. Coding and user interface
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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is funded in association with the Lero Research Centre and the Immersive Software Engineering programme. Faculty: Dr. Roisin Lyons - Kemmy Business School; Prof. Chris Exton – CSIS; Dr. Clare
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education and research. The applicant is expected to have: A MSc or equivalent degree in Microelectronics, Computer Science, Electrical Engineering, or a similar field; Expertise in your field of study, in
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following asset criteria: a) Evidence of project leadership, project management, grants or awards; b) Experience in leading collaborations; c) Experience with advanced computing platforms, systems
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should possess an M.Sc./M.Eng. degree in one of the following fields: Electrical and Electronics Engineering, Telecommunications Engineering or Computer Science/Engineering. Experience: The candidate
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(masterexamen) of 120 credits or a Master’s degree (magisterexamen) of 60 credits in Electrical Engineering, Communication Engineering, Engineering Physics, Computer Engineering or similar, with a strong
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degree (magisterexamen) of 60 credits in computer science, computer engineering, electrical engineering, or another relevant field* You will need strong written and verbal communication skills in English
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collaborative settings and wish to play a key role in an EU-funded project with researchers from multiple countries? If so, this PhD position could be a good opportunity for you. This project focuses
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civil/electrical/control engineering or mathematics or related study programs with a solid basis in choice modelling and/or reinforcement learning, with knowledge of MATSim is advantageous. Description