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transparent models. The Privacy-aware transparency decisions research group (led by Prof. Vicenç Torra) conducts research in data privacy for data to be used for machine and statistical learning. It is well
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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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applications and applications sent by email will not be considered. Application deadline: Oktober 15, 2025 For questions, please contact: Prof. Tünde Fülöp, Subatomic, High Energy and Plasma Physics Email: tunde
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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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/loe ). Your work will primarily be under the guidance of Prof. Daniel Simon (https://liu.se/en/employee/dansi08 ), Organic Bioelectronics group leader at the Laboratory of Organic Electronics, with
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-fidelity qubits operations Design and implementantion of automatic calibration techniques for fast tune-up Implementation and benchmarking of quantum algorithms About you You have a relevant PhD deegree
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include writing scientific manuscripts, presenting project outcomes, and to supervise students at basic and advanced level. The research project will be coordinated by Prof. Rickard Ignell at SLU Department
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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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for scientific purposes. The postdoc will work with Prof. Daniel Metcalfe (Umeå University, Sweden) and Dr. David Bartholomew (Botanic Gardens Conservation International, Brazil), and collaborators within
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including, among others, Prof. Maria Riveiro. You will focus on developing and evaluating explanations from AI systems. Your work includes teaching or other departmental duties, up to a maximum of 20% of full