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team and actively participate in the DIPONI project (“Digital Transformation in Polymer Processing: Interoperability and Machine Learning Solutions for Process Optimization and Sustainability
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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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Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta
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of computer science or using computer vision methods Excellent knowledge of the development and implementation of methods in the field of digitization, artificial intelligence, machine learning and/or 2D/3D imaging and
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omics, environmental, and chemical data, using machine learning and explainable AI. Depending on your background, interests, and evolving project needs, your work may focus on one of these areas or bridge
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). Knowledge of Docker and machine learning is considered a plus. Knowledge of standard bioinformatics tools for analyzing and interpreting Next Generation Sequencing data. Excellent oral and written
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such as ecology, economy and social sciences. ZMT aims to use data science tools, including computer vision and deep learning, for the study of rapid changes in tropical coastal socioecological systems
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organised, accurate in their experimentation and adaptable to learning new techniques. Primaryresponsibilities Preparation and processing of animal histological samples, including organ embedding, cutting and
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or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is
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machine learning/artificial intelligence methods in combination with complex network analysis tools to predict and model interactions between food and biological systems Further scientific development