166 machine-learning-"https:"-"https:"-"https:"-"https:" positions at KINGS COLLEGE LONDON
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
-quality robotics research in the areas of robot grasping and manipulation, kinematics and mechanisms, sensing, and human-robot interaction. Within CORE, SAIR focuses on multimodal machine learning for human
-
to the project’s scope, such as mechanistic interpretability of LLMs, robustness verification of machine learning models, and conformal inference. Applicants should demonstrate scientific creativity, research
-
environment. Strong computer skills (proficient with MS WORD, Excel and web-based applications). Eye for detail and ability to accurately document findings in written reports. Able to learn and work to SOPs and
-
for analysis of large-scale bulk and single cell data sets Strong understanding of statistical modelling, data normalisation and machine learning methods applied to biological datasets Experience with data
-
general audience Desirable criteria Experience with machine learning Coding in PyTorch Evidence of published work simulating soft tissue mechanics Experience supervising junior team members and PhD students
-
global partnerships. With world-renowned researchers and a passionate student body, we are always encouraging innovative and progressive collaboration, as well as new ways to work and learn. Further
-
, Nutritional Sciences and Women's Health cluster) for REF was rated as world-leading or internationally excellent. We use this expertise to teach the next generation of health professionals and research
-
for King’s Engineering. We offer undergraduate and postgraduate education, with a distinctive approach, combining traditional teaching methods with modern, project-based learning, catering for the needs of our
-
general audience Desirable criteria Experience with machine learning Coding in PyTorch Evidence of published work simulating soft tissue mechanics Experience supervising junior team members and PhD students
-
, GraphPad Prism. Familiarity with state-of-the-art Machine Learning techniques, with the ability to apply them to bioimage analysis. This includes practical experience with relevant ML frameworks such as