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significant modeling challenge. This project addresses that challenge by combining machine learning with constitutive modeling, while ensuring adherence to physical laws. Although the primary focus is on large
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Master's degree in computer science, computer engineering, or equivalent. Demonstrate proficiency in English (reading, writing, speaking). Show the ability to work independently and in a team, as
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will use advanced evaluation techniques, data mining, and generative machine learning models to create an active learning cycle to identify materials with adequate properties. Promising materials will be
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Optimal Transport for Optimization and Machine Learning Appl Deadline: 2026/02/04 11:59PM (posted 2025/12/19, listed until 2026/02/04) Position Description: Apply Position Description Doctoral student in
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matter of the position and the duties that the position will involve. Because the teaching at the Department is given in English, applicants must have a documented ability to teach in English. Since
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generative machine learning models to create an active learning cycle to identify materials with adequate properties. Promising materials will be synthesized, characterized and evaluated in lab. This will help
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Systems, Internet Systems and Computer Networks, Robotics, Machine Learning and AI, Automatic Control, or Mathematical Modelling and Optimization. Documented good profiency in software development. Good
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support the teaching activities courses at KTH and further develop methodologies and algorithms for the quantum computer simulators. Qualifications Requirements A graduate degree or an advanced level
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computational methodologies, ranging from atomistic and electronic-structure–based materials modeling and characterization, via machine-learning and high-throughput methods, to ab initio calculation
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, tightly collaborating research groups conducting research and education in Robotics and AI, Intelligent Autonomous Systems, Robot Learning, Machine Learning, Human-Robot Interaction and Natural