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evolve with the development of SciLifeLab as a national resource, and responsibilities may shift accordingly. Due to our highly collaborative environment, occasional tasks outside the primary scope
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science in carrying out concrete AI projects. This includes compiling, organizing, and sharing key datasets, assisting with resource allocation proposals, conducting machine learning workflows, and
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sciences in carrying out concrete AI projects. This includes compiling, organizing, and sharing key datasets, assisting with resource allocation proposals, conducting machine learning workflows, and
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other experts within the Support for Computational Resources unit at NBIS and related organisations, notably SciLifeLab, National Academic Infrastructure for Supercomputing in Sweden (NAISS), and EuroHPC
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robots -Distributed task planning for collaborative missions -Behaviour tree based multi agent collaboration -Reactive task allocation in large scale missions For further information about a specific
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teaching and at least 50% research. In addition to this, time is allocated for professional development in accordance with local agreements, departmental duties by agreement, and other tasks commonly
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research environment, internally, nationally and internationally and thus 50% of employment is allocated for research and professional development. The duties within this allocation include research, Ph.D
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and machine learning to tackle the complexity of force allocation and motion planning under uncertainty and actuator failures. The project combines theoretical research in stochastic optimal control
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for school choice, segregation, resource allocation, and educational and career choices. The research group uses a wide range of methods, including field and survey experiments, register data studies, and
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evolution and direct manipulation of resource allocation patterns, this project aims to explore somatic and germline mutation rates from a life-history perspective, to determine whether they are integrated