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Mälardalen University (MDU) is the youngest university in Sweden. In line with our vision, to be a progressive and collaborative University where we shape a sustainable future together, we wish to make a difference. Do you want to be involved and contribute to our development? Together, we can...
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Engineering, Electrical Engineering, Information and Communication Technology, Engineering Physics or Engineering Mathematics. Additional requirements In order to complete the doctoral programme in question
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240 higher education credits in Applied Mathematics, Applied Physics, Electrical Engineering, Mechanical Engineering, or a related field. A strong mathematical foundation and excellent academic
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)? The study of the potential and limits of efficient computation is about foundational, mathematical, research, but research results in computational complexity theory have had major impact in other areas
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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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qualifications: To be eligible for this position, you must have (or be close to completing) a Master’s degree corresponding to at least 240 higher education credits in Applied Mathematics, Applied Physics
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publications, presentations). Qualifications You need: A PhD degree in computer science, mathematics, or engineering physics, preferably with a focus on data analysis, AI trustworthiness, human robotics
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description The candidate will work on problems at the intersection of mathematical statistics, machine learning, and generative modeling, particularly for sequential data arising in complex dynamical systems
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qualities and suitability. Your workplace This ELLIIT -funded project will be conducted at the Physics, Electronics, and Mathematics (FEM ) division within the Department of Science and Technology (ITN
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and development Generative AI models for sound, music, visuals, 3D graphics, or movement Projects related to Generative AI Background in mathematics and statistics of Deep Learning What you will do