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Subject description The PhD work will be carried out within European Innovation Council funded project Bioinspired Singlet Fission Photon Multipliers (BioSinFin). The goal of BiosSinFin is to use
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of Molecular Mechanisms and Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. More information about the total announced post-doctoral positions within in
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based on advanced methods in statistical modelling, machine learning (including artificial neural networks) and geographic information analysis. You will be part of two dynamic research environments
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systems, and machine learning. While the initial focus of the position is on this project, we offer significant opportunity for the applicant to develop their own independent research trajectory in
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such as energy, industry, consumption, and urban development. At the research frontier, the application of AI and machine learning is enabling novel pathways for sustainability transitions. These include
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the time you start (you can apply before they are met e.g. during your PhD). A doctoral degree (PhD or equivalent) in an area relevant to the announcement. Everyone is welcome to apply but due to regulations
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collaborate with multiple stakeholders and conduct applied research in silviculture, forest ecology, pathology, policy and planning. We teach bachelor, Masters and PhD level courses addressing all
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on developing methods for the verification and validation of systems that embed machine learning or generative models, addressing challenges such as non-determinism, data drift, and explainability. The project
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military service. What you will do The majority of your working time is devoted to your own research, in collaboration with other postdocs and PhD students, as well as collaborating groups. As a Postdoc you
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, attention to detail, and good communication skills are essential for success in this role. Flexibility and a willingness to learn are also important, as NBIS continually adapts to meet the evolving needs