36 civil-engineering-"https:"-"https:"-"https:"-"https:" research jobs at King's College London
Sort by
Refine Your Search
-
Listed
-
Program
-
Field
-
of a collaborative team, led by Dr Sarah Morgan at the School of Biomedical Engineering and Imaging Sciences. The School is a world leading centre of expertise in AI for healthcare, providing
-
to evaluate what the sessions achieve, and lead the specification of a public-facing demonstrator built with design-engineering collaborators at Imperial College London (Prof Rafael Calvo). They will also work
-
TACT is an interdisciplinary fellowship reimagining how technology can support communication for people with communication disabilities. Combining perspectives from HCI, human-AI interaction
-
. PharosAI has been awarded £18.9M in funding from the Department for Science, Innovation, and Technology, and cash and in-kind contributions bringing the total funding to £44M. About The Role We are seeking a
-
groups, conducting research assessments using digital technology methods (smartphones and virtual reality), and managing large datasets. You will work closely with the lived experience advisory panel who
-
activities, including helping with literature review of the use of digital technology for people with mental illnesses. This is a full-time post (35 hours per week), and you will be offered a fixed term
-
About us King’s College London is an internationally recognised research-intensive university. The Department of Physics, within the Faculty of Natural, Mathematical & Engineering Sciences, hosts
-
Postdoctoral Research Associate to work within its research group. Our team uses interdisciplinary approaches for studying pancreas development and islet cell engineering from pluripotent stem cells
-
. The Wellcome Bioimaging project to accelerate cutting-edge bioimaging technology development, is a five-year cross-disciplinary programme, led by Professor Maddy Parsons from the School of Basic & Medical
-
learning, with proven experience working with large language models: including fine-tuning, prompt engineering, and evaluation of LLM outputs 3. Experience or demonstrated interest in uncertainty