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both academic research and industrial applications. In addition to theoretical research, the work might involve implementing new algorithms in the SCT tool Supremica, which is developed by the Automation
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experimentally verified results is a necessary: - Autonomy with collaborative intelligence - Distributed task and motion planning - Predictive collaboration with heterogeneous teaming - Multi-agent navigation in
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, the work might involve implementing new algorithms in the SCT tool Supremica, which is developed by the Automation group. Main responsibilities Conduct research in collaboration with senior researchers and
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researcher position will focus on the following key areas, where a proof of previous work with experimentally verified results is a necessary: - Autonomy with collaborative intelligence - Distributed task and
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Machine Learning Integration Develop and implement machine learning algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC
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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite
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computational algorithms to enable regenerative cell therapies. Now, we are seeking a highly driven postdoctoral researcher to contribute to our ambitious mission. Division The Division of Biomolecular and
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day to apply is 14 September 2025 Linnaeus University has the ambition to utilize the qualities that an even gender distribution and diversity brings to the organization. Please apply by clicking
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value the qualities that an even distribution of age and gender, as well as ethnic and cultural diversity, can contribute to the organization. Application The application is to be completed online. Please
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in their computation. We want to understand the fundamental principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose. The group collaborates with several