13 machine-learning-and-image-processing-"RMIT-University" positions at Empa in Switzerland
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industrial partner, you will design and implement innovative architectures for real-time detection and control of laser processes. This interdisciplinary role combines artificial intelligence and machine
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product quality attributes, such as remaining shelf life. Process measured sensor data of commercial cold chains, analyze data for variability, and reformat data in databases. Use the simulation-based
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specifically to XRD-PDF (pair distribution function). The project is linked to crystalline and amorphous alloys, and in an industrial context to process design by establishing the structure-property relationship
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statistical evaluation Machine learning analyses: implementation of established and new workflows Coordination of activities with Consortium partners, including presentation of results at consortium meetings
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. You will perform microstructural characterization of dry coated electrodes using physical and machine learning based methods and the electrochemical assessment of the electrodes in battery cells. Your
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campaigns (one to two weeks per year) Holder of a valid car driving license Our offer We offer a fully funded PhD student position (3 years, full time) at Empa, the Swiss research institute for materials
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is a plus. Enthusiastic about learning new techniques and both independent and as a team member. Our offer We offer a full-time postdoctoral position at Empa in Dübendorf, Switzerland, starting as soon
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solid-state batteries. One of research topics is the method of flash-lamp annealing ( FLA, also called intense pulsed light or photonic curing ), which is used for thermal processing of thin films with
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match the chemical, mechanical, and morphological properties of native bone. The role of the PhD student at Empa will be the development of synthesis processes using light-based 3D printing of hydrogel
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material processing and assembly strategies. Your tasks Study the triggered enzymatic crosslinking and disassembly of single biopolymer systems. Characterize the evolution of the structure of the biopolymers