Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
plant production techniques. Alongside identifying and validating propagation techniques and peat-free alternatives, we will develop new AI search tools and explore cultural shifts in horticulture
-
. You will also develop and review policies and procedures and will prepare tender documents for the renewal of key assets ensuring compliance with procurement rules and procedures. Candidates should hold
-
salts and ionic liquid by collaborating with a growing research team while conducting their own investigations. The role holder will have the opportunity to contribute to the development of funding
-
, they will liaise with colleagues across the University to manage the identification, development and preparation of REF impact case studies and statements. They will be the central contact point
-
calls, training and development programmes, annual meetings and day-to-day administrative tasks. Working as a key part of the NOBLE team, you will be required to organise, plan and deliver projects
-
and external regulatory requirements. The School of Medicine recognise the importance of continuous professional development and therefore the importance of providing opportunities, structured support
-
placement within Siemens Digital Industry Software. Project Overview The project focuses on developing and integrating ML techniques to enhance wall treatments for under-resolved boundary layers in
-
simulation, composites manufacturing and advanced sensing techniques. The project will provide opportunities to develop skills in these areas and contribute to the development of the next generation composite
-
research building on previous research from the Silvi research group. The research will focus on the development of novel reactions based on photoredox-radical chemistry. The new radical processes will be
-
the noise associated with near-term quantum devices. This in turn offers an exciting new dataset from which it will be possible to use machine learning to train a more accurate functional for use in density