57 computer-programmer-"https:" "https:" "UNIS" "https:" "https:" "https:" "https:" "Dr" positions at The University of Manchester in United Kingdom
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in the groups of Dr Florence Hardy and Prof Anthony Green, University of Manchester, as part of the cross-institutional BioAID Doctoral Training Programme, including world-leading experts from Queen's
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synthesis of new materials. For the robotic additive manufacturing, the lab has a house-developed Laser-Kuka cell with 16kW IPG laser and wire/powder feeding systems. The lead supervisor, Dr Yuze Huang
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under the supervision of Dr Mehrdad Vasheghani Farahani from Department of Chemical Engineering, with co-supervision by Professor Ian Kinloch from Department of Materials. The successful candidate will
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the main supervisor, Dr Samuel Draycott – samuel.draycott@manchester.ac.uk for this project before you apply. Please include details of your current level of study, academic background and any relevant
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, computer science, or a closely related discipline (typically first-class or high 2:1, or equivalent; Master’s welcome) • Strong programming skills (for example Python, MATLAB, C/C++) • Strength in at least two of
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supervised by Dr Ed Pickering and Prof Tim Burnett. Please contact ed.pickering@manchester.ac.uk if you wish to apply. Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s
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master’s (or international equivalent) in a relevant science or engineering related discipline. To apply please contact the main supervisor, Dr Carbone - paola.carbone@manchester.ac.uk . Please include
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undertake an interdisciplinary programme combining polymer synthesis, materials characterisation, rheology and mechanical testing, and in vitro drug release studies, supported by quantitative analysis and
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, cutting-edge research facilities, and real-world datasets. The successful candidate will work under the supervision of Dr. Steph Flores (steph.flores@manchester.ac.uk ) at the Department of Chemical
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facilities, and real-world datasets. The successful candidate will work under the supervision of Dr. Steph Flores (steph.flores@manchester.ac.uk ) and co-supervised with Dr. Carlos Avendaño (carlos.avendano