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experimental and suited for candidates who enjoy hands-on research, learning new techniques, and working across disciplinary boundaries. Your competencies We seek a highly motivated candidate with a strong
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tools or functional genomic information or OMICS to improve genomic prediction models. The persons hired will collaborate with industry partners, teach at undergraduate and graduate levels, and supervise
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employees, 500 PhD students and 160 technical/administrative employees who are cooperating across disciplines. As a Postdoctoral researcher, you will be working at Aarhus University Hospital or another
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intelligence within grid-connected power converters and variable-frequency motor drives with edge computing and machine learning capabilities. We offer a multidisciplinary, international, and friendly atmosphere
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bring strong research expertise and strong technical skills within remote sensing and ecology, notably lidar processing. The successful candidate should have: Required: A PhD degree with a publication
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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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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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recombinant minibinders for migraine-associated receptors. The project aims to advance deep learning–based molecular generation and structure-guided design for therapeutic innovation. We seek a highly motivated
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19 Mar 2026 Job Information Organisation/Company Aarhus University Research Field Engineering Other Researcher Profile First Stage Researcher (R1) Recognised Researcher (R2) Positions PhD Positions
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implement state-of-the-art data science principles into dental practice. While our primary focus is on the use of deep learning in (dental) imaging, our work expands into any type of data (e.g. tabular data