70 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral research jobs at Technical University of Denmark in Denmark
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(e.g., based on physiological signals or direct inputs from occupants) and developing algorithms, including machine learning methods. The work will include statistical modelling, data-driven modelling
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Job Description These days, the inner workings of molecules and materials can be probed and modelled by advanced simulation tools on modern computer architectures. However, the routine applications
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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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computational and experimental techniques. Play an active role in education and outreach in protein design, including contributions to teaching and mentoring activities. You must have a PhD in a relevant field
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an independent research career. Responsibilities and qualifications We are looking for a creative and ambitious researcher with a PhD within cellular biology, molecular biology, bioengineering or similar. You must
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microscopy, and mammalian cell culture will be an advantage. As a formal qualification, you must hold a PhD degree (or equivalent). We offer DTU is a leading technical university globally recognized
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chatbots and other virtual assistants that can help students learn more effectively or prepare for exams, or support teachers in repetitive tasks. We are looking for a highly motivated and experienced
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qualification, you must hold a PhD degree in computer science, software engineering, biomedical engineering, data science, or a similar field. Your project management skills include: Experience in technical
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levels, ranging from BSc, MSc, PhD to lifelong learning students. We have about 300 dedicated employees. Read more about us at www.energy.dtu.dk Technology for people DTU develops technology for people
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interest and documented skills and experience in using computer-based tools to analyse, simulate and predict capture performance of active and passive fishing gears. A track record of publishing in peer