22 phd-rehabilitation-engineering-computer-science PhD positions at The University of Manchester
Sort by
Refine Your Search
-
for over a century, the fundamental physio-chemical processes governing tree initiation and propagation remain inadequately understood, representing a significant scientific and engineering challenge
-
systems. Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline. *Solid background in
-
-treatment facilities, and biorefineries. Feedstock choice, regional dynamics, and process side-streams all affect costs, energy use, and emissions. This PhD project will develop advanced computational models
-
. Applicants should hold a first-class (or equivalent) degree in a relevant engineering or science discipline (upper second class may be considered depending on the bachelor's/master's dissertation project
-
a highly motivated candidate with: A first-class or upper second-class degree (or equivalent) in Materials Science, Chemistry, Physics, Chemical Engineering, or a related discipline. Experience in
-
to increase each year. Tuition fees will also be paid. Home students are eligible. A funded PhD studentship is available in the field of computational inorganic chemistry. The project will involve prediction
-
, this platform has potential applications in broader tissue engineering contexts, including implantable biomaterials, wound healing, and regenerative therapies for age-related conditions. This 3.5 year PhD project
-
, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline. Strong background/skills on machine learning, mathematics, probabilistic
-
. The Centre sits within the Department of Mechanical, Aerospace and Civil Engineering at UoM and performs advanced modelling and technical innovations in the field of laser-based advanced manufacturing
-
Engineering, Computer Science or related disciplines. Experience in autonomous system, manufacturing/robotics and machine vision development will be an advantage. To apply please contact the supervisor, Dr Kun