55 phd-computational-"IMPRS-ML"-"IMPRS-ML" positions at Chalmers University of Technology
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PhD students in the Automation group, with the primary goal of qualifying for a future academic career. Contribute to research projects within discrete-event systems, supervisory control theory, and
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photonics by developing and implementing experimental methods, maintaining and improving laboratory facilities, and collaborating closely with researchers, PhD students, and external partners. As a Research
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aimed at building a high-performance quantum computer based on superconducting circuits. Our team includes a dynamic mix of PhD students, postdocs, and senior researchers working collaboratively
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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
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, you must hold a PhD (awarded no more than three years prior to the application deadline*) in computer science, maritime transportation, or a related field, with a strong foundation in mathematics and
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the sustainability performance of the built environment. Job description We are looking for three student assistants to support the PhD project Measuring to Manage: A Methodological Framework for Quantifying Plastic
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-scale computational methods, and bioinformatics. The division is also expanding in the area of data science and machine learning. Our department continuously strives to be an attractive employer. Equality
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scientific research publications. Your profile Required qualifications PhD in Chemistry, Chemical Engineering, Physics, Catalysis, Materials Science or equivalent (awarded no more than three years prior
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facilities that are highly aligned with the goals of the project. Who we are looking for We seek candidates with the following qualifications: To qualify for the position of postdoc, you must have a PhD degree
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to develop solutions with real world relevance and impact. This project will be carried out in close collaboration with researchers from the Division of Material and Computational Mechanics at IMS and the