70 algorithm-development-"The-University-of-Edinburgh"-"The-University-of-Edinburgh" positions at University of Bath
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
(or equivalent related field) with experience with cryogenic systems and/or sensor development for a KTP Associate position based on-site at Druck Ltd , Leicester, LE6 0FH. About the role As the Knowledge Transfer
-
About the role This exciting opportunity at the Brunel Centre involves joining a ground-breaking initiative at the forefront of regional economic research and development. Embedded in a
-
quality research, you will be expected to develop strong and effective working relationships with project teams and partners and external stakeholders. You will be responsible for: Life cycle assessment
-
performance, using the University's bespoke publishing platform, built and developed in-house. You’ll also have the opportunity to work closely with the Head of Marketing and our digital agency, to manage the
-
Behaviour research group The successful candidate will join an active research group focused on the development and application of mathematical methods to complex systems, with a particular emphasis on
-
publications, from literature reviews and developing research instruments to drafting content for technical reports and peer-reviewed papers. Supporting project coordination for this large-scale international
-
data-driven approaches to proactively identify and support students who may be at risk of disengagement. We are seeking an Engagement Analytics Manager to lead the implementation and development of our
-
Policy Manager, you will: Develop and implement research policies and procedures at institutional level. Provide clear guidance to researchers on external legislation affecting research (eg Human Tissue
-
training and career development for all research staff in the MHRG. You will work under the supervision of world-leading clinicians and academics. The Bath MHRG is partnering with the Universities of Bristol
-
challenge. This project builds on our preliminary work using reinforcement learning to develop control strategies and aims to develop an advanced controller based on reinforcement learning that will optimise