Sort by
Refine Your Search
-
Listed
-
Program
-
Field
-
testing, numerical modelling, and machine learning (ML) aided design approach will be adopted, utilising the respective expertise in Brazil (testing and wind tower design experience) and the UK (modelling
-
analysis will include legal doctrinal and empirical (i.e. legal computational and qualitative) methods that are specifically designed to capture and interpret internal (i.e. legal) and external (i.e
-
will join a team of probabilistic modellers and machine learning researchers developing new collaborative AI principles and methods. This is an exciting topic which inspires new problems in fundamental
-
discipline is required, alongside suitable experience in research methods and techniques to work in a fast-paced research programme. International candidates are advised to carefully read the University
-
This research assistant post provides an exciting chance to support a Cancer Research UK funded programme of research that aims to improve access to lung cancer early detection for individuals with
-
to identify relapse signatures using active and passive digital monitoring and data collection methods. The post-holder will have some experience and interest in research on psychosis or in severe mental health
-
Assistance Programme Exceptional starting annual leave entitlement, plus bank holidays Additional paid closure over the Christmas period Local and national discounts at a range of major retailers As an equal
-
environments. · Expertise in computer literacy, MS Office packages and electronic databases. · Proven excellence in handling and entering data including an understanding of data protection and confidentiality
-
at The University of Manchester. What you will get in return: Fantastic market leading Pension scheme Excellent employee health and wellbeing services including an Employee Assistance Programme Exceptional starting
-
The post holder will support a research programme funded by the Shreeve Foundation investigating the causes of pancreatic cancer risk through the analysis of large-scale molecular and