235 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in Denmark
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bachelor’s, master’s and PhD degree programs within animal science and veterinary medicine. We offer a lively, engaged and innovative learning and study environment, which is closely integrated in the research
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include: Skills in mathematical modelling and machine learning of relevant physical glacier processes (ice sheet and mountain glaciers), with proficiency in MATLAB/Python/Fortran, and related software tools
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qualifications at PhD level. How to apply Your application must include the following: Application, stating reasons for applying, qualifications in relation to the position, and intentions and visions
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be employed by the Department of Biology at Aarhus University and work in the Section for Microbiology at this department. The section employs 12 permanent scientific staff and ~20 PhD students and
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hold a PhD in bioacoustics, engineering, physics or neuroethology, or similar. Experience with trained bats and toothed whales and handling or tagging of wild conspecifics is an advantage. You must have
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-evolutionary simulation. The position is available from 1 March 2026 or as soon as possible thereafter and is for 2 years. Qualifications and competences Applicants must have a PhD degree or equivalent or have
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) Recognised Researcher (R2) Positions PhD Positions Country Denmark Application Deadline 16 Oct 2025 - 12:00 (Europe/Copenhagen) Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Feb 2026 Is
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, TESPy, or similar libraries. Strong programming skills in Python or MATLAB, including use of scientific libraries (e.g., NumPy, Pandas, Matplotlib, etc). Experience with machine learning (e.g., Scikit
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. Research-based teaching in GNSS, geodesy, and surveying. The teaching must be conducted in Danish and English at bachelor’s (BSc) and master’s level (MSc) Co-supervision of BSc, MSc, and PhD projects Public
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, coordinated by Aalborg University and funded by the EU’s Horizon Europe program. The project aims to improve fiber-to-fiber textile recycling across Europe by developing smarter sorting systems, recycling