23 machine-learning "https:" "https:" "https:" "https:" uni jobs at KINGS COLLEGE LONDON
Sort by
Refine Your Search
-
of Mental Health & Psychological Sciences, and our NHS and industry partners. We particularly welcome candidates whose expertise complements existing departmental strengths in machine learning, multimodal
-
an international research profile in areas such as: Systems security, Security engineering, Security testing, Computer forensics, AI for security and privacy, Security and privacy of AI. Our department addresses
-
complements existing departmental strengths in machine learning, multimodal data integration, digital phenotyping, and trial emulation using electronic health records. This is a full-time post (35 hours per
-
have: A PhD (or equivalent) in a relevant discipline (e.g., biostatistics, machine learning, computer science, clinical informatics, natural language processing). Strong skills in data analysis and
-
Robotics to develop research in the field, e.g., robot design, control and mechatronics; Publication record in robotics and machine learning, e.g., ICRA, IROS, RSS, CoRL, T-RO, CVPR, ICML; Excellent verbal
-
such as: Systems security, Security engineering, Security testing, Computer forensics, AI for security and privacy, Security and privacy of AI. Our department addresses computer science challenges from a
-
have an international profile in research and education in any of the following areas: systems security, security engineering, security testing, computer forensics, AI for security and privacy, and
-
Details: informatics-hod@kcl.ac.uk Where to apply Website https://www.timeshighereducation.com/unijobs/listing/404894/reader-in-computer-… Requirements Additional Information Work Location(s) Number
-
About us The Department of Informatics is looking to appoint a Reader in Computer Vision Education. This is an exciting time to join us as we continue to grow our department and realise our vision
-
forensics, AI for security and privacy, Security and privacy of AI. Our department addresses computer science challenges from a broad perspective. Faculty members regularly publish in and serve on the program