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to the design, modelling, simulation, validation, and optimization of electric vessel power systems, with strong emphasis on battery-based propulsion, onboard microgrids, EMS algorithms, and real-time validation
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of fertilizers into the soil. The project aims to develop and optimize innovative porous carriers to enhance fertilizer efficiency, controlled release, and sustainability in agricultural applications
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required to develop and demonstrate single-photon light detection and ranging (LiDAR) systems by integrating in‑house single‑photon detectors. The role will assess various LiDAR configurations, optimize
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operationally safe position in real-time. This research focuses on real-time multi-objective optimization of wells, that may be achieved with a mixture of algorithmic and machine-learning approaches. Updating
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models, and foundation models Strong programming skills in Python and deep learning frameworks such as PyTorch Experience with large-scale experiments, model optimization, and performance analysis
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Demonstrated expertise in small-molecule synthesis, optimization, and structure–activity relationship (SAR) studies Strong problem-solving skills and the ability to work independently within a collaborative
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across the following research areas: Predictive machine learning Robust and stochastic optimization Learning-enabled control and reinforcement learning Power system operations, planning, and electricity
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nanoparticle catalyst, and optimization of enantioselective metal-catalyzed reactions. The role will focus on autocatalysis particularly related to amplification of enantiopurity. The candidate should also have
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Conversion of Biomass” is looking for a Postdoctoral Researcher in Development of automated self-optimizing small-scale flow processes. The primary objectives are generation and optimization of automated flow
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, and performing characterization and optimization. Key Responsibilities: Design and assemble a compact mid-infrared laser system capable of generating high-average-power and high-peak-power femtosecond