22 computer-programmer-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"CEA-IRIG" positions at The University of Manchester
Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
machine learning and conventional optimisation techniques. 2. To design and optimise magnonic primitives for wave-based neuromorphic computing, including programmable devices enabling nonlinear activation
-
advances in additive manufacturing and computational design. Architected lattice metamaterials—structures whose properties arise from geometry rather than composition—offer unprecedented opportunities
-
Sustainability (RAPTOR). The successful candidate will be part of a cohort of PhD students across four universities (Manchester, Liverpool, Surrey, Suffolk) working in a national programme with 18 industrial
-
also researched by the recently commenced multi-million MOSFET (The Maturing Optimised Solutions for Aerospace Technology) research programme lead by RR in collaboration with UoM and an electrical
-
decarbonization of existing maintenance and decommissioning of assets. Programme structure (1+3)* Year 1 (Taught component): All students spend the first year at The University of Manchester undertaking taught MSc
-
(wind, solar, geothermal, tidal, hydrogen) and nuclear (fission and fusion), and to support the decarbonization of existing maintenance and decommissioning of assets. Programme structure (1+3)* Year 1
-
programme as part of BioProcess, the Biocatalysis and Protein Engineering Centre for Sustainable Synthesis (bioprocess-idla.ac.uk), which has strong partnerships with the chemical industry. They will thus
-
scheduling under multi-objective KPIs (rate, latency, detection, localisation, etc.) Reconfigurable/programmable radio environments and system/network-level antenna design Theory with guarantees (convex/non
-
backgrounds such as AI, computer vision, computer graphics, machine learning, robotics, wearable technologies, textile engineering, fashion technology, digital fashion, or related areas are encouraged to apply
-
backgrounds such as AI, computer vision, computer graphics, machine learning, robotics, wearable technologies, textile engineering, fashion technology, digital fashion, or related areas are encouraged to apply