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Field
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advances the mathematical foundations, algorithms, and real-world applications of epistemic uncertainty in machine learning, with a strong focus on imprecise probabilities, uncertainty representation and
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with simulation techniques, energy efficiency models, large-scale energy consumption data, machine learning techniques and interpretation (unsupervised); - Education, experience and research orientation
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have recently received their Ph.D. in sociology, human geography, or a related discipline; Demonstrated expertise in spatial analysis, machine learning, or other advanced quantitative methods
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on emerging privacy-preserving techniques such as homomorphic encryption, secure multi-party computation and federate learning. Key Responsibilities: Conduct advanced research in the areas of privacy-preserving
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at the intersection of mitochondrial biology, functional genomics, and machine learning. This interdisciplinary initiative focuses on discovering, decoding and engineering mitochondrial microproteins (mito-MPs) with
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researcher in natural language processing and large language models to work with a team from multiple disciplines of machine learning and artificial intelligence to develop multimodal large language models
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of what microscopes can achieve. You will create and apply sophisticated algorithms, physics-based simulations, and machine learning models to process complex data from our cutting-edge imaging systems
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productive manner. Knowledge of legal implications in clinical practice and documentation. Knowledge of performance improvement and evidence-based practice. Basic computer skills. Ability to assess, plan
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for employment without regard to race, color, sex, gender identity, sexual orientation, religion, creed, national origin, ancestry, age, protected veteran status, disability, genetic information, military service
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disciplines, including human-robot interaction, robot learning, soft robotics, computer vision, and agricultural robotics. About the PhD project: We are looking for a highly motivated and talented PhD research