10 computer-engineering-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Max-Born-Institute" Fellowship positions in Denmark
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Postdoctoral Research Fellow - Human-Centered AI for Data Visualization at Computer Science, Aarh...
Visualization at Computer Science, Aarh... Employer Aarhus University (AU) Location Aarhus, Midtjylland (DK) Salary Competitive Closing date 1 Sep 2026 View more categories View less categories
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The Department of Computer Science at Aarhus University (Denmark) invites applications for a 36-month Postdoctoral Research Fellow position focused on Human-Centered AI for Data Visualization. The
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The Department of Computer Science at Aarhus University (Denmark) invites applications for a 18-month Postdoctoral Research Fellow position focused on Human-Centered AI and Data Visualization. The
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. Your competencies Applicants must have a strong technical background, ideally in computer science, software engineering, human-computer interaction, Medialogy, AI, machine learning, or a related field
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PhD Scholarships in Engineering of Quantum Light Sources and System Architecture for Photonic Qua...
engineering of system architecture for photonic quantum information technology. The position is offered within the framework of the EU Horizon Europe MSCA Doctoral Network “A Photonic Quantum Computer
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degree programs at Aarhus University, especially but not exclusively related to AI, https://digitalcurriculum.au.dk in collaboration with colleagues from CED and NAT Join as a co-teacher in a few of the
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Department of Computer Science at Aarhus University (Denmark) invites applications for a 4-month Postdoctoral Research Fellow position with focus on Cryptography. The starting date is November 1st
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perspectives from the learning sciences, Computer-Supported Collaborative Learning (CSCL), Computer-Supported Collaborate Work (CSCW), Human-Computer Interaction (HCI), Participatory Design, and Artificial
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partners at UniProt, SIB Swiss Institute of Bioinformatics, and Aalborg University. The project aims to unlock decades of scattered QTL knowledge from the plant genetics literature by combining AI-assisted
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on enabling and hindering factors for scaling, including market conditions, policy frameworks and local infrastructures. You will work closely with colleagues in the Materials Science and Engineering