29 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" positions at KINGS COLLEGE LONDON in United Kingdom
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
level. Successful candidates will teach and supervise students who are serving officers and civil servants in the UK and allied armed forces and partners. There are also opportunities to contribute
-
Shrivenham and will undertake high-quality scholarship and support a range of professional military and security education courses at the postgraduate level. Successful candidates will teach and supervise
-
system may hold clues to how psychosis and other psychiatric disorders are caused and how people respond to treatments. We will investigate blood and cerebrospinal fluid from patients and use machine
-
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
-
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
-
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
-
establishing a strong academic track record. You may have worked in MRI research previously or have strong computational / AI / machine learning skills used in other areas of research. Essential criteria PhD
-
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
-
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
-
on quantitative phenotyping via generative modelling of quantitative MRI data. This exciting PhD position combines advanced machine learning with medical imaging physics to develop next-generation tools