14 machine-learning-"https:"-"https:"-"https:"-"https:"-"U.S" uni jobs at Lancaster University
Sort by
Refine Your Search
-
prototyping with access to Lancaster's high-performance computing facilities. Essential Requirements • PhD in Machine Learning, Computer Science, Computational Neuroscience, or related field
-
: 0828-25 Lecturer in Technology Enhanced Learning in the School of Social Sciences, Lancaster University (Temporary one-year post). The School of Social Sciences seeks to appoint a full-time Lecturer in
-
Sociology Location: Bailrigg, Lancaster, UK Salary: £39,906 to £48,882 Part time-Fixed Term Closing Date: Sunday 05 October 2025 Interview Date: To be confirmed Reference: 0691-25 The learning
-
: 0832-25 This is a full-time (1 FTE) position. We are seeking to appoint a Learning Developer to join our well-established team at Lancaster University. The successful candidate will be responsible
-
experience of machine learning, multiwavelength imaging and data analysis are encouraged to apply. Prospective candidates are encouraged to contact Dr John Stott (j.p.stott@lancaster.ac.uk ) for further
-
revision techniques, and participating in teaching reviews and quality assurance processes. We are particularly looking for candidates who are passionate about creating an outstanding lab-based learning
-
bringing together observations and global atmospheric models using innovative statistical and machine-learning approaches. It will provide the first clear attribution of how different physical, chemical and
-
a PhD in mathematics or a related discipline and be able to demonstrate previous research experience in using mathematical machine learning and AI methods, or applied mathematics, to solve challenging
-
bringing together observations and global atmospheric models using innovative statistical and machine-learning approaches. It will provide the first clear attribution of how different physical, chemical and
-
life and prepare them for future study. You will work with participating students to monitor their progress and provide constructive feedback to maximise their learning so that they are able to achieve