14 data-"https:"-"https:"-"https:"-"https:"-"UNIV" research jobs at Imperial College London
Sort by
Refine Your Search
-
Listed
-
Program
-
Field
-
outputs with electrochemical performance data from a variety of analytical techniques (e.g. diffusion, conductivity, power density etc) (D) Highly confident and articulate with outstanding communication and
-
neurodegenerative disorders. The role centres on enabling high-quality, reproducible analysis across prescription data, longitudinal clinical records, wearable time-series data, and multi-omics datasets, with
-
gas challenges. You will particularly gain skills in the principles and practice of running mechanistic clinical studies from practical aspects through to handling data. In addition to supporting
-
the protocols used to control and communicate sensitive patient information, all the way up to interventional devices and systems for personalised healthcare. We are particularly looking for an IC
-
these representations to guide the identification, by debate, of (non-)compliance to PRLs of LLMs and T2Is; O3) in the case of non-compliance, using information conveyed in the debates to enforce PRLs on LLMs and T2Is
-
‑bounded turbulence. This short, intensive 9‑month position offers an exciting opportunity to advance fundamental turbulence research using DNS/LES and data-driven optimisation techniques. In this role, you
-
by Professor Ara Darzi, while working towards a PhD degree . The research project will entail project design, experimental work in addition to data analysis and reporting the results in peer-reviewed
-
of national health care provision through data-informed resource allocation and strategic planning and investment. The post is funded by the Wellcome Trust, and the post-holder will join a team based across
-
and optimisation but not limited to data driven monitoring for control and operation. You must have a good master’s degree in electrical engineering, with Power and Control Engineering major
-
by the Medical Research Council, that aims to improve the standardisation, modelling, and analysis of prescription data in Parkinson’s disease, with the goal of predicting medication-related side