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Biology, Computer Science or related studies) Experience in Python with PyTorch (or equivalent) programming Experience in sequencing data analysis Basic knowledge in machine learning Experience with linux
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. Specifically, the PhD candidate is expected to contribute corpora preparation (collection and organizing the annotation), use machine learning approaches for irony detection, and testing for experimental and
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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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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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highly motivated doctoral student to join an ambitious project aimed at building machine and deep learning models to study the genetics of human disease. Funded as part of the Helmholtz AI program, the
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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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. The Leibniz-LSB@TUM comprises a unique and world-leading research profile at the interface of Food Chemistry and Biology, Chemosensors and Technology, and Bioinformatics and Machine Learning. Leibniz-LSB@TUM’s
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mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High
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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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-learning prediction models” with the following focus areas: Design and development of methods for drifter detection in self-learning AI models Evaluation using real data sets from photovoltaic systems and