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research reports and technical papers for publishing. 3. Investigates the feasibility of applying a wide variety of scientific principles and theories. 4. Maintains substantial knowledge of state-of-the-art
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, optimization, and the experimental validation of communication-aware robotic systems. Position Requirements: Ph.D. in Robotics, Electrical Engineering, Telecommunications, Computer Engineering, Control
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cuantitativo. Capacidad para trabajar con grandes conjuntos de datos y entornos computacionales. / Experience in data science, data management and optimization, and machine learning and AI techniques. Strong
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innovative solutions for future communication networks and sensing-enabled services. Job description The successful candidate will contribute to research on energy-efficient network design, optimization, and
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data processing using ImageJ/Fiji or equivalent software. Knowledge of amphiphilic block copolymer self-assembly is highly desirable. Experience in integrating molecular catalysts, nanoparticles
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/ Deep Learning Knowledge of: Active learning, Bayesian optimization Reinforcement learning or decision-making systems Experience with: Python ecosystem (PyTorch, Scikit-learn) Data pipelines and
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research is carried out in close collaboration with external partners, both nationally and internationally, and contributes to knowledge development and innovation. Through our collaboration platforms, we
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optimization. You enjoy hands on laboratory work, iterative troubleshooting, and mentoring junior researchers. You are collaborative, organised, and committed to producing high quality scientific outcomes. About
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expertise in high-performance clusters are required. Knowledge, Skills, and Abilities: · Knowledge in advanced statistical theory and methods. · Strong optimization and computational skills
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Engineering and production optimization Documented mathematical, analytical and problem-solving skills. Good knowledge of statistics, AI/ML, and mathematical modeling and programming. Good knowledge in academic