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) group at Aalborg University. The position is for two years and combines theoretical research, algorithm development, simulations, embedded implementation, laboratory experimentation, and industrial
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of two years. About the Project The successful candidate will advance the algorithmic and theoretical foundations of reinforcement learning applied to complex, high-dimensional dynamical systems
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one day a week on campus. Job description The computational biologist will be expected to: Lead the development of acoustic detection and classification algorithms for marine mammals. Evaluate algorithm
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thereafter. We are seeking a highly motivated quantum algorithms researcher to develop advanced computational methods for solving partial and ordinary differential equations (PDEs and ODEs) with applications
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. The tasks include battery cell characterization and modelling based on laboratory tests, and development of algorithms for estimating the charge level, health, and power capability which includes robustness
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and corrective feedback. You will apply advanced algorithms for machine learning, multimodal biosignal processing, and human-state inference, working with shared-control strategies and electrotactile
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in e.g. qubit measurements and quantum error correction algorithms. The core responsibilities include modeling, simulating and designing components and chips for photonic and neutral atom quantum
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: Designing lightweight TTA algorithms that can recalibrate models at the edge under strict latency and computational constraints. Efficiency and Reliability: Balancing the trade-offs between adaptation
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interface, and all the way to quantum algorithms and applications. The long-term mission of the programme is to develop fault-tolerant quantum computing hardware and quantum algorithms that solve life
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, or similar languages Background in machine learning or deep learning methods Knowledge of genomics, transcriptomics, evolutionary biology, and plant biology is an advantage Familiarity with large biological