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Field
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with the latest sensors (camera and LiDAR sensors), is available for the work. What you will do Development of algorithms for 3D multi-object tracking based on heterogeneous sensor data fusion (standard
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challenging, and new theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers
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processes related to carbon cycling in the soil-plant system Experience with Bayesian inference and machine learning is an asset Ability to work independently and cooperatively as part of an interdisciplinary
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and reduction Development and application of big data analytics for large X-ray data sets Application of Bayesian methods to X-ray data Combinatorial analysis of various data from complementary
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project objectives. Establishing and maintaining effective scientific collaboration with the co-hosting research groups, contributing to a cross-disciplinary team environment. Preparing, documenting, and
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seeking to fill the following position Research Scientist (m/f/d) for Long-Term Benthic Dynamics (Tenure Track / full time – part time: minimum 80%) at the department Marine Research as per 01 Dezember
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, ocean, marine ecosystem, and impact models of different complexity and will include both traditional and new ocean modelling approaches with the final objective of delivering: (i) coordinated and
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and collection research on two types of objects with epistemological and application-oriented research. The goal is twofold: first, to develop IT- and AI-supported methods for museums and other
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analysis problems, especially tracking the motion of objects, which are driven by real applications in life science research Developing solutions to integrate large foundation models into microscopy image
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Bayesian belief networks; Experience in scenario development approaches, e.g. SSPs; Experience in the application of R-based analytical tools for qualitative or semi-quantitative modelling, incl. RQDA