568 machine-learning "https:" "https:" "https:" "https:" "https:" "Cardiff University" positions at University of Sheffield
Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
with core data analysis and professional skills that are necessary for bioscience research and related non-academic careers. https://www.yorkshirebiosciencedtp.ac.uk Project Description: The oestrogen
-
areas as well as equip you with core data analysis and professional skills that are necessary for bioscience research and related non-academic careers. https://www.yorkshirebiosciencedtp.ac.uk Project
-
Arrangements Part -Time. AMRC, Wallace Way, Rotherham, S60 5TZ Monday - Friday, 6:00am - 9:30am, 17.5 hours per week. Line Manager Cleaning Shift Supervisor Our Website http://www.sheffield.ac.uk/efm
-
must have an International English Language Testing System (IELTS) average of 6.5 or above with at least 6.0 in each component, or equivalent. Please see this link for further information: https
-
to apply: Please complete a University Postgraduate Research Application form available here: http://www.shef.ac.uk/postgraduate/research/apply Please clearly state the prospective main supervisor in
-
Direct reports None Our website https://sheffield.ac.uk/eee For informal enquiries about this job contact Sam Whitehouse, School Technical Manager on sam.whitehouse@sheffield.ac.uk. Next steps in
-
data analysis and professional skills that are necessary for bioscience research and related non-academic careers. https://www.yorkshirebiosciencedtp.ac.uk Project Description: Join a groundbreaking
-
to progress to £33,951) Work arrangement Full-time Line manager Team Support Manager Direct reports N/A Our website https://staff.sheffield.ac.uk/rpi For informal enquiries about this job contact Alison Hunt
-
Work arrangement Full-time Duration Fixed term to 31 March 2029 Line manager Dr Richard Thackray, Senior Lecturer in Metallurgy and Metals Production Direct reports N/A Our website https
-
. The overarching aim of the project is to use machine learning methods to understand why many people who are referred for treatment will drop out prematurely. To do this, two studies are planned. One will use a