154 data-"https:"-"https:"-"https:"-"https:"-"I.E"-"UCL" positions at Cardiff University
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
achieve its objectives. Work with others to make recommendations to improve our ways of working. Gather and analyse data (e.g. business travel, staff and student travel, fleet mileage data) so that informed
-
experience in relevant techniques, laboratory housekeeping and maintaining records under the Human Tissue Act. For further information candidates should contact Professor Matthias Eberl (eberlm@cardiff.ac.uk
-
. Ability to communicate conceptually detailed and complex information effectively and professionally with a wide range of people 7. Ability to work well within a team to achieve the team’s objectives, but
-
customer service; and communicating complex information effectively. They should also be capable of setting up and improving administrative processes, influencing key stakeholders, and planning and managing
-
to and which will enhance performance. Gather and analyse data working with Graduate Outcomes and Target Connect to inform decisions, establishing trends and patterns in data and creating reports as
-
Information Management System (SIMS), Timetabling software (Syllabus Plus), and Virtual Learning Environment including Learning Central and Business Objects. • To provide administrative support to
-
the University on changes to financial systems. · Undertake a variety of administrative duties to support the Financial Systems and Data team. · Instruct and guide other employees across the University to support
-
to deliver greater levels of success Customer Service, Communication and Team WorkingAbility to communicate detailed and complex information effectively and professionally with a wide range of people
-
within the specialist field of data science and/or building performance. The CLCBE team have been commissioned by Neath Port Talbot County Borough Council to carry out monitoring and evaluation as part of
-
advanced computer modelling (in silico), through robot driven testing of implanted knees (in vitro), to 3-dimensional X-ray imaging of moving patients (in vivo) with Machine Learning driven analysis