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This PhD position is part of the WASP-WISE NEST project RAM³ – a multidisciplinary research effort at the intersection of machine learning and materials science. The project brings together PhD
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-Channel Evaluation of Cellular Dynamics (TIMED) , is a 5-year collaboration between researchers at Chalmers University of Technology, Uppsala University, and Karolinska Institute. About us The Department of
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We are offering a PhD student position in machine learning (ML) theory, focusing on new methods for training models with a limited amount of data. The student will be a part of a new NEST initiative
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(WASP). The NEST project, Solid Polymer ElectrolytE Discovery (SPEED) , is a 5-year collaboration between researchers at Chalmers University of Technology and Uppsala University. About us The Department
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scheduling in shared workspaces - Shared autonomy and predictive learning - Human-robot teaming in distributed decision-making Sensing and perception - Collaborative perception and localization - Learning
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independently. You have the capacity for learning new things, working systematically, and showing flexibility where required. Collaborative skills, accuracy, and subject-related expertise are emphasised
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development and analysis in other projects within the department. Your tasks include collaborating with colleagues and stakeholders in the design and validation of tools, performing data and literature analysis
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spatial data of ecosystems and human activities, and more holistic analyses of socio-ecosystems. Your will collaborate with colleagues and stakeholders and contribute to scientific reports and publications
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control and its integration with learning-based motion prediction under uncertainty. - Validate methods through simulation and collaboration with industrial partners (Volvo Cars and Volvo Group). - Publish
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at the Division of Fluid Dynamics, within the Department of Mechanics and Maritime Sciences at Chalmers. The project is carried out in collaboration with Vattenfall Research and Development, and is part of