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particle trapping and related measurement techniques. Relevant skills include understanding of fundamental principles, design, optimization, computational electromagnetic, mechanical and thermal modeling
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colleague? Apply now! Education • PhD in Computer Science, Telecommunications, or a closely related field. • Solid knowledge of mobile networks and 5G systems, with practical understanding of RAN optimization
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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experiments, with emphasis on negative ion mode Develop and optimize fragmentation strategies for peptide analysis under collisional- and electron-based dissociation regimes Investigate gas-phase chemistry of
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communications; iv) System-level design and optimization. The related domains and topics for each of these research areas that we would like to attract excellent researchers to work on are the following: Radio
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the research team in the area of Swarm Intelligence, Reinforcement Learning and Optimization Techniques. As a Postdoctoral researcher, you will: Lead cutting edge research in Swarm Intelligence and Machine
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biomedical and biological data, including developing and optimizing models to predict disease progression and create realistic patient profiles; Building and optimizing pipelines for pre-processing and
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(training provided). Design and optimize protocols for new biophysical assays to address complex cancer biology questions.– Example project: Science, 2023 Writing and submitting NIH training grants, including
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methods (e.g., PCA, PLS-DA, clustering, neural networks) to enable automated, polymer-specific classification. Optimize workflows for high-throughput imaging and real-world sample variability, minimizing
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scientifically diverse team to achieve assigned research objectives. Candidates with experience in the following areas are especially encouraged to apply: Development and optimization of next-generation sequencing