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Field
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Student assistant (m/f/d)-Multi-Modal Sensor Fusion, Object Detection in Clutter and Object Tracking
bring to the table Enrolled student High motivation and initiative Very good English language skills Experience with Isaac Sim / Lab Experience in computer vision and deep learning is an advantage
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Senior Scientist / Group Leader on Bioinformatics / Computational Biology on RNA Regulation in Disea
, and validate computational findings Apply machine learning and statistical modeling techniques to identify patterns and predict functional impacts of RNA modifications Contribute to publications
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. To this end, we develop system concepts, build them and carry out experiments for customers. You will be part of our team of four research assistants and eleven student assistants and learn hands-on project
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vision models Experience with event-based cameras, neuromorphic vision concepts, spiking neural networks, and/or neuromorphic computing is a plus Experience with, or willingness to learn, ROS 2 for robotic
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methods in AI and machine learning, contributing directly to state-of-the-art research with high industrial relevance. Your Qualifications A strong background and Master's degree in Computer Science, AI
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technology. What you will do As part of an internship, we offer you the opportunity to deepen your interest and knowledge in the field of machining. You will learn how to use CNC machine tools and manufacture
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Sustainable and Modular Networks (SMN) working group operates in an international
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, Rehabilitation, Biostatistics, Python, R, SQL, Machine Learning, Real-World Data, TUM Hospital The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally
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the application and development of modern methods in data science and machine learning, especially with unstructured data. A good command of the German language is essential due to the focus of the academy project
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of reaching climate neutrality by 2050. By leveraging characterisation, multiscale modelling, machine learning, and numerical optimisation, the project seeks to craft a magnetic multiscale modelling suite