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some background in one or more of the following areas: Mathematical Optimization / Operations Research Reinforcement Learning, Machine Learning, and/or Multi-agent systems Game Theory Algorithms
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distribution modelling Experience with spatial analysis and mapping tools (e.g., QGIS, ArcGIS, or spatial packages in R/Python) Interest or experience in applying AI or machine learning methods to ecological
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, mathematics, physics, remote sensing and machine learning. Experience and skills · Strong interest in modelling, model-data integration, and remote sensing data analysis. · Knowledge of programming, remote
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advanced analytical technology. In our laboratories we have state-of-the art 3D printers and CNC machines as well as NMR spectrometers. Key responsibilities: Design and manufacture microfluidic chips and
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computer sciences. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in several engineering programmes at bachelor’s and master’s levels, as
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for the position. Preferred selection criteria Scientific publications are an advantage Experience in research project works Good knowledge and experience in the use and development of machine learning algorithms
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here as machine systems that can produce novel and creative results. Several important questions are raised: to what extent are generative AI systems genuinely creative? How do they differ from human and
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large datasets, and applying AI approaches (e.g. machine learning, image segmentation, multimodal AI data integration) will be considered advantageous. Strong skills in communicating scientific results
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM) You will be responsible for Developing new machine learning algorithms for microscopy image
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opportunity to learn, develop and apply a range of cutting-edge modeling and computational techniques. You will work in an interdisciplinary, cutting-edge, fast-paced research environment, interact with