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involves close collaboration with the Department of Architecture, Design, and Media Technology and is part of a larger project involving at least two PhD candidates. The candidate’s workplace will be in
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the Department of Architecture, Design, and Media Technology and is part of a larger project involving at least two PhD candidates. [CB1] The candidate’s workplace will be in Aalborg. Your work tasks The
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, and protein structure prediction by artificial intelligence algorithms. The goal is to generate functional models of multimeric protein complexes and how they assemble as a guide to understand disease
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. Qualifications Applicants must hold a PhD or equivalent qualifications in a relevant field, such as Child-Computer Interaction, Human-Computer Interaction, Learning Sciences, Educational Technology, Computer
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microscopy, and protein structure prediction by artificial intelligence algorithms. The goal is to generate functional models of multimeric protein complexes and how they assemble as a guide to understand
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deliverables Support supervision of MSc and PhD students related to the project Qualifications You must have a PhD degree (or equivalent) in robotics, mechatronics, control, or a related field. We expect you to
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Master's and PhD students. Candidates will be responsible for creating a collaborative work environment within and outside QGG that integrates novel innovative research programs towards the green transition
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grant applications Experimental work will include molecular engineering, protein characterization, and cellular functional validation in engineered T cells. We are looking for a candidate who: Holds a PhD
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contributing to computational model development The position is primarily computational and AI-driven, with close interdisciplinary collaboration. Qualifications We are looking for a candidate who: Holds a PhD
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innovation across electronics, materials science, and artificial intelligence. What we expect Applicants should hold a PhD in electronic engineering (the degree should have been completed within the last 5