73 phd-studenship-in-computer-vision-and-machine-learning PhD positions at Technical University of Munich in Germany
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for three PhD positions to be filled on August 1st 2025 to enlarge our research team working on NLP for medical applications. PhD Positions in NLP for Medical Applications The Chair of Software Engineering
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: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong knowledge in Machine/Deep Learning with experience in discriminative models
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journals. Close collaboration with team members and colleagues. Essential qualifications: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong
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passionate about creating a pioneering map where calories are located and microbially transformed in a soil aggregate? Then this exciting PhD opportunity is for you! The project is part of the SoilSystems SPP
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05.01.2025, Wissenschaftliches Personal The group “sustainable energy materials” offers a position to pursue a PhD (f/m/d) in Electrochemistry / Automation About us: Our group “Sustainable Energy
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diagnosis, and knowledge of the operation of helicopter systems. • Confident handling of Python and common data science tools. • Knowledge of high-performance computing and machine learning. • Fluency in
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analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team
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, agricultural sciences with a focus in economics, or related disciplines - strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, sta-tistics, machine learning
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the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission analysis, and infrared thermography
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networks self-organize their architecture. We are looking for a PhD student (m/f) to join our team at the TUM. Task Flow networks are a fundamental building block of life. Transport by flow is the main task