10 mathematics-computer-science PhD scholarships at Chalmers University of Technology
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of neural networks and other symbolic techniques with applications ranging from mathematics to cognitive science, and often in cross-disciplinary collaborations. In this project the PhD student will work
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fields: Robotics Computer Science Electrical and Computer Engineering Mechanical Engineering Applied Mathematics Applied Physics Statistics and Optimization A strong background in robotics, machine
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This is a call for a PhD position in the Data Science and AI division at the Department of Computer Science and Engineering (CSE) , Chalmers University of Technology. The department
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student, you must have a master's level degree in a relevant field (e.g., physics, mathematics, or computer science). Equivalent requirements apply to individuals with an education earned outside of Sweden
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Engineering, Computational Engineering, Engineering Mathematics, Engineering Physics or similar* You will need strong written and verbal communication skills in English Documented experience (education/courses
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mathematical foundations in theoretical computer science. Good verbal and written communication skills in English. Swedish is not required for this position. Chalmers offers free language courses for those
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the Swedish National Infrastructure for Computing (SNIC) and the Chalmers Centre for Computational Science and Engineering (C3SE). Learn more about the project and the research: Project overview Due
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15 full-time researchers offers a stimulating and supportive environment to learn and grow. Your profile Required qualifications: Undergraduate degree in Engineering, Physics or Mathematics with strong
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(masterexamen) of 120 credits or a Master’s degree (magisterexamen) of 60 credits in Electrical Engineering, Communication Engineering, Engineering Physics, Computer Engineering or similar, with a strong
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. The applicant should have strong background in mathematical foundations of computer science and experience in Python programming. Previous experience in deep learning, reinforcement learning, or explainable AI is