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in research project management, and a relevant publication track record. Application deadline: March 20th, 2026 at 23.59 (CET) Place of work: Dept. of Computer Science, Aarhus University, Åbogade 34
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This is a full-time (37 hours/week) on-site role located at Åbogade 34, 8200 Aarhus N, Denmark for a Postdoctoral Fellow at the Department of Computer Science, Aarhus University. The postdoctoral
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The Department of Computer Science, Aarhus University, invites applications for a full-time 2-year Postdoctoral position, starting 1 April 2026– or as soon as possible thereafter. Position and
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next‑generation insect camera traps with on‑device (edge) computing for real‑time detection and classification Collaborating in an interdisciplinary team spanning ecology, computer science, engineering
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of open data and open science. Your profile The ideal candidate should have: A PhD in environmental engineering, ecology, environmental science, biology, data science, computer science, or a closely related
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, physics, computer science, applied mathematics, or similar Required competences Strong background in image processing and analysis, especially Deformable image registration and 3D segmentation methods
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qualifications include: Ph.D. in Computer Science, Computer Engineering, Electrical Engineering or a related field; Strong background in Deep Learning (e.g., Transformers, foundation models); Strong programming
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level, e.g. in medical physics, physics, biomedical engineering or computer science. It is mandatory that your PhD degree is on a topic relevant for this specific position, e.g. in medical image-based
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Are you interested in Robotics and can you contribute to the development of the project Dynamics and Control of Robotic Handling and Maintenance of Fusion Reactors? Then the Department of Mechanical and Production Engineering invites you to apply for a 20-month postdoc position. Expected start...
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engineering, geoinformatics, computer science, or a related field with a focus on deep learning applied to remote sensing or geospatial data Documented experience with deep learning model development (e.g