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Organisation Job description Postdoctoral position: ManufActuring contRol Sonicare (MARS) Due to the complexity of the assembly process anomalies can occur, that lead to unplanned downtime and sub
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dynamic environment where scientists, engineers, clinicians, and industry partners collaborate to shape the future of cancer treatment technologies. Your colleagues You will join a multidisciplinary team of
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thirty-two research and industry partners, HyTROS seeks to fast-track the scaling up of green hydrogen in the Netherlands. For the establishment of a strong and safe hydrogen infrastructure, it is
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advanced treatment planning. You’ll work at the forefront of translational research, in a dynamic environment where scientists, engineers, clinicians, and industry partners collaborate to shape the future
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or a related engineering field. Industry experience in the domain of engineering is a strong plus; Experience with bio-microfluidics engineering (Computer-Aided Design and micromilling), biosensing and
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𝐏𝐨𝐬𝐭𝐝𝐨𝐜𝐒𝐞𝐩𝐚𝐫𝐚𝐭𝐢𝐨𝐧𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐞𝐬𝐟𝐨𝐫𝐋𝐢𝐪𝐮𝐢𝐝𝐚𝐧𝐝𝐆𝐚𝐬𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐬𝐏𝐫𝐨𝐝𝐮𝐜𝐞𝐝𝐛𝐲𝐂𝐎2 𝐄𝐥𝐞𝐜𝐭𝐫𝐨𝐥𝐲𝐬𝐢𝐬 Job description To meet environmental targets for CO2 emissions set forth, alternative, low-carbon emission approaches to existing manufacturing processes for base chemicals
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postdoctoral researcher, you will use various techniques to investigate fiber-reinforced structures in nature (i.e., fungi), including additive manufacturing, computer simulations, materials testing, and
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mathematics and computer science, generating new knowledge in these fields and conveying it to trade, industry, and society at large. CWI is an internationally oriented institute, with 160 scientists from
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, such as virtual machines, containers and network configurations; project-based experience (e.g. EU, ESA, Industry); natural curiosity and a passion for new subjects and research areas in space security and
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targeting performance improvement) is finding interest in the academic community and applied developments in industry. Recent studies have indicated interest in a reinforcement learning (RL)-based controller