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plate array microscope for simultaneous time-lapse video microscopy, enabling high-throughput single-cell analyses of rapidly migrating cells. You will be responsible for Develop new machine learning
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action recognition, and enable seamless collaboration between humans and machines. Long-Term Human-Technology Evolution: investigate the longitudinal impact of human-technology interaction on learning
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recognition, and enable seamless collaboration between humans and machines. Long-Term Human-Technology Evolution: investigate the longitudinal impact of human-technology interaction on learning, behavior, and
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fully funded PhD position in the area of safe data-driven system identification for cyber-physical systems, offered by our research group at the intersection of control theory, machine learning, and
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contribute Completed an excellent doctorate in computer science Proven track record of excellent publications Expertise in cryptography and/or machine learning Leadership capabilities and ability to mentor
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and evaluation of human-machine interactions as well as the design of complex socio-technical systems. The Automated Driving Research Group addresses topics related to the interaction between users and
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hash functions for image recognition OSINT and crawling, social media and the dark web / cryptocurrencies Machine learning for data analysis AI security: Attacks on deep learning (classifiers, LLMs) and
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team — comprising biologists, engineers, computer scientists, and medical researchers — develops next-generation computational models to interpret complex biomedical data across multiple scales. Our
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skills in Python, Java, C++, etc. A solid foundation in generative AI, machine learning, and related areas. An Interest in eye-tracking technology, Computer Vision, Speech/ Language Processing, VR, and AR
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Oxford Nanopore Technologies (ONT). Your role will be central in creating and applying bioinformatics and machine learning tools to analyze long-read data and decipher cap-specific signals from raw