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Supervisors: Professor Richard Hague1 , Professor Chris Tuck1 , Dr Geoffrey Rivers1 (1 Faculty of Engineering) PhD project description: Inkjet printing allows multiple materials to be 3D-printed
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of Electrical Engineering and Computer Science School of Art and Design Course language German and English Financial support No Structured research and supervision Yes Research training / discussion Yes Career
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students and supervising professors); implementation of the planned research program, evaluation and interpretation of the results, elaboration and presentation of the research; participation in lectures
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3-year PhD studentship: Scaling-Up Functional 3D Printing of Devices and Structures Supervisors: Professor Richard Hague1 , Professor Chris Tuck1 , Dr Geoffrey Rivers1 (1 Faculty of Engineering) PhD
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future autonomous instrument control and self-directed experimentation will be developed, recognizing the challenge presented by the integration of multiple complex systems. Coding and user interface
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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computer literacy, good inter-personal communications skills. Desirable skills: A Master in Health Economics with experience in cost effective analyses. Funding notes The three year studentship covers UK
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will, in addition, sharpen your didactics skills through experience as a teaching assistant. You must hold a two-year master's degree (120 ECTS points) in Robotics, Electrical Engineering, Computer Science
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. The project will be supervised by Associate Professor Martin Hansen (DTU Sustain), and co-supervised by Professor Hans Peter Arp (NTNU Chemistry), Senior Scientist Anna Rosenmai (DTU Food), Veerle Jaspers (NTNU
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qualifications As our new colleague in our research team your job will be to develop novel computational frameworks for machine learning. In particular, you will push the boundaries of Scalability, drawing upon