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Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig | Leipzig, Sachsen | Germany | 3 months ago
, the relation between human cognition and machine learning, and others. The position is offered for three years. The starting date is, in principle, flexible, while we aim to get started as soon as possible
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key agroecosystem variables. These variables include cover crop growth, crop nitrogen, yield, and tillage practices. You will develop novel algorithms to integrate data-driven machine learning and
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analysis using advanced statistics or other quantitative analyses. Scientific diving certification. Knowledge of hand tools and machine / woodshop tools. Brief Description of Duties: The Postdoctoral
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programming, interfacing hardware, and developing machine-learning methods highly desirable. The researcher will join an Argonne funded project with interdisciplinary team of material scientists, computer
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analysis using advanced statistics or other quantitative analyses. Scientific diving certification. Knowledge of hand tools and machine / woodshop tools. Brief Description of Duties: The Postdoctoral
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calculations, sample size determinations and statistical analysis plan. 3. Apply machine learning approaches to integrate diverse datasets collected from study participants to identify subtle differences
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Research Focus We are offering a Postdoctoral position in graph machine learning, algorithms, and graph management with particular focus on: Modeling real-world spatio-temporal energy networks Developing
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for opportunities abroad. These grants present an excellent opportunity for recently minted scholars to deepen their expertise, to acquire new skills, to work with additional resources, and to make connections with
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time, we promote a supportive culture that fosters knowledge exchange, learning, creativity and scientific excellence. The PI, the group, the Department and university-wide initiatives (e.g., the Durham
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, biochemical, cell, and tissue biology method skills. Experience in using computational analysis (biostatistics, machine learning, data science, physics, or a related field). We value diversity and strongly