97 big-data-and-machine-learning-phd Fellowship positions at University of Nottingham in Uk
-
the project, you will work in close collaboration with the team designing and testing the reactors to validate your simulation outputs, and your data will directly feed to the research undertaken by another
-
Requirements Essential: • PhD (or near completion) in Chemical Engineering, Environmental Engineering, Sustainable Process Engineering, or a closely related field. • Demonstrated experience in techno
-
PhD (or equivalent) in food science, nutrition, or a related discipline, with experience in in vitro digestion, specifically using the INFOGEST static digestion model, nutritional analysis (minerals
-
Requirements Essential: • PhD (or near completion) in Chemical Engineering, Environmental Engineering, Sustainable Process Engineering, or a closely related field. • Demonstrated experience in techno
-
are currently performed in our laboratory. Applicants must be highly motivated and self-driven, with a PhD in molecular biology or a related area of biological science. The successful candidate should ideally
-
PhD, EngD (or equivalent) in chemical engineering, chemistry or a related discipline. The post is offered on a full time (36.25 hours per week), fixed term contract until 30 June 2027. Informal
-
the sector, yet a lack of gender-disaggregated data combined with the predominance of gender-blind programming means that workplace protections often miss key threats to women’s wellbeing. The research aims
-
Applications are invited from qualitative researchers with a PhD (or close to completion) for the position of Research Associate/Fellow within the School of Health Sciences. You will be part of a
-
to explore own research interests. We are looking for a researcher with experience of data-intensive projects involving simulations or observations, good knowledge of galaxy formation physics, and the ability
-
systems to work across several industry relevant projects. MAS has a large intra-disciplinary team of researchers, engineers, technicians, support staff and academics who work together to deliver research