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on the following areas: Development algorithms and their software implementation in Python and PyTorch Validation of results and comparative analysis of proposed method with baseline approaches Qualifications You
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, or equivalent. You must also have a documented proficiency in written and spoken English. Examples of knowledge and skills that may be of use in the position include evolutionary and population
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methods relying on machine learning, artificial intelligence, or other computational techniques. The specific subject area is focused on the ecological and evolutionary processes generating and shaping
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models and algorithms in Python, with documented experience in PyTorch. The applicant should be knowledgeable with neural networks and furthermore have a strong drive towards performing fundamental
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involves evaluating the economic benefit (Value of Information) of these new inventory methods compared to traditional approaches. Duties and Responsibilities: Algorithm Development: Develop and validate
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solutions based on conceptual theory and empirical eco-evolutionary, molecular, and genetic data that can meet the needs of current and evolving plant production systems. For more information about the
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methods relying on machine learning, artificial intelligence, or other computational techniques. The specific subject area is focused on the ecological and evolutionary processes generating and shaping
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, experience working with the PyTorch framework, documented ability to develop algorithms and implement them in efficient code, and experience in statistical modeling, optimization or numerical methods, as
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multiphase phenomena. The study will combine theory, algorithm development, and computational modeling, with the goal of advancing scalable hybrid approaches for next-generation fluid simulations. Who we
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to extract knowledge from data, modelling large-scale complex systems, and exploring new application areas in data science. Areas of interest include but are not limited to models and algorithms for knowledge