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Field
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to design, optimize, and scale-up of electrolyzer systems to use for recycling spent battery materials. Key Responsibilities Design & Development • Lead the design and scaleup our electrolyser systems
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
that the University of North Carolina at Chapel Hill strives to instill in every unit, department, and program at this great University. The Graduate School supports graduate students in almost every program across
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Application Deadline 23 Sep 2025 - 21:59 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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Per Week 35 Is the job funded through the EU Research Framework Programme? European Union / Next Generation EU Reference Number 7131 Is the Job related to staff position within a Research Infrastructure
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materials integration, nano-enabled coatings and multifunctional composites. The main duties foreseen are: Design, synthesis and optimization of Cu-Metal-Carbon interfaces in copper based nanocomposites
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. Research areas include Representation Learning, Machine learning and Optimization on graphs and manifolds, as well as applications of geometric methods in the Sciences. This is a one-year position with
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variety of conditions that are not optimal growth conditions. The survival data of pathogens under these conditions (growth matrices + sub-optimal growth temperatures + antimicrobial stresses) will also be
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vulnerable to hardware-level threats, including side-channel attacks, fault injections, etc., particularly when optimized for performance. This Research Fellow position focuses on AI security in the context
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) Country Morocco Application Deadline 19 Sep 2025 - 00:00 (UTC) Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is
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Engineering, Computer Science, Applied Mathematics or equivalent. Strong background in machine learning, convex optimization, or distributed systems. Prior experience in federated learning, edge computing