Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
-termWorking TypeHybridAvailable for SecondmentNoClosing Date14-Jun-2024 A four-year PhD Studentship in Pharmacometrics and Machine Learning funded by the UKRI EPSRC and GSK is available within the Institute
-
frameworks (MOF), a reticular class of materials for their use as excipients. The project also involves elements of machine learning models for screening appropriate excipients from FDA data base. Person
-
costs of their project. We will support two students, one in the area of health data science/epidemiology/statistics and the other specialising in applied machine learning and informatics. The closing
-
. Project Title: Applying machine learning algorithms to datasets to predict outcome for paediatric solid organ transplant recipients. Review of the Key Literature: Predicting outcomes after paediatric solid
-
communication skills and preferably experience of using Python and machine learning in an applied context, preferably in a healthcare environment. This role is a part time (7.3 hours per week) fixed term
-
collaborative, interdisciplinary setting. You must hold (or be about to receive) a PhD in Statistics, Data Science, Computer Science, or a related discipline. Substantial experience applying machine learning
-
have a PhD in a relevant area as well an appropriate track-record of high quality research outputs in the field of Artificial Intelligence / Machine Learning, and clear and ambitious plans for future
-
the department. Areas that we aim at covering include but are not limited to: AI and Machine Learning, with interest to ground, aerial, and marine robots. About you You should have a PhD in Robotics, AI, or a
-
will initially be focused on developing and evaluating machine learning and statistical modelling tools to predict and classify disease trajectories using large scale health records databases to answer
-
language understanding and generation, which further enhances the potential of user simulators using language models as backbones. This PhD project is part of an ongoing collaboration with researchers from UCL and the