Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
Exactly: A Bayesian Approach. The project aims to address the challenges in pooling inference, by developing and implementing either exact or asymptotically exact Monte Carlo algorithms in collaboration
-
methods for load identification and modelling to infer load behaviour from measurements at the grid supply point (GSP). Your work will help determine whether new load types need to be defined in the CLM
-
research profile and reputation and that of the University of Glasgow/School/Research Group/area, including establishing and sustaining a track record of independent and joint publications of international
-
modelling to infer load behaviour from measurements at the grid supply point (GSP). Your work will help determine whether new load types need to be defined in the CLM framework to accommodate new components
-
science or equivalent experience in compiler design and/or interactive theorem proving, and a track record of relevant scientific publications, whereas at the Research Assistant level must hold a MSc in Computer
-
establishing and sustaining a track record of independent and joint publications of international quality in high profile/quality refereed publications, enhancing the research impact in terms of economic
-
desirable Track record of contributing to research publications Strong skills in designing research materials and analysing mixed-methods data Confident in using Microsoft Word, Excel, Outlook, PowerPoint
-
to finance sectors. A track record of first author and/or collaborative publications in high quality journals and international conferences (Finance, AI, NLP related publications). Strong relevant research
-
, development, and evaluation of interactive platform features as part of the research methodology, collecting and analysing data on user engagement through tools for feedback, co-creation, and project tracking
-
About the role This is an exciting opening for an Adult Physician with demonstrable expertise in controlled human infection models an exceptional track record in grant funding and publication