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degree and PhD in Forestry Engineering, Biology or Ecology; PhD less than 6 years ago, with a thesis in the project areas. Demonstrate (i) activities at universities abroad in the project specialties and
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position is embedded in a vibrant research environment that includes several PhD students and postdoctoral researchers. The project is a close collaboration between the Computer Vision Group at Chalmers
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at the interface using computer simulations. At the beginning simulations will be used to model polymeric particles, such as microgels. With these simulations we will study how the individual particle
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also have or be close to completing a PhD in any of the following areas as well as the will and commitment to learn relevant topics from the other areas: Statistical and machine learning, mathematical
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computer. The WACQT team at Chalmers currently has about 100 members (faculty, permanent research staff, postdoctoral researchers, PhD students, and undergraduate students). WACQT is committed to promoting
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interdisciplinary environment, first-class mechanical and electronics workshops, and access to the King’s core facilities network. King’s is committed to an inclusive, supportive research culture. Researchers
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participate in knowledge exchange with public authorities and industry and will be involved in teaching and supervising students at the BSc, MSc, and PhD levels. Qualifications for a postdoc position: Academic
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independently, has a passion for AI and its applications, and is willing to learn new technologies. The candidate should have a PhD in Computer Science or a closely related field. Relevant background and skills
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the interfacial strength, nano-scale 3D structure and residual stresses in advanced power electronic materials (INTERVENE), and is fixed-term of 18 months. Power electronics is a major technology sector for the UK
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: PhD or equivalent degree in Robotics, Computer Science, Machine Learning, AI, Control Engineering, or a related field. Excellent programming skills and experience with related tools and software. A