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Knowledge, Skills, and Abilities The applicant must have strong programming skills in Python, and experience in at least one of the following areas: virtual reality development, machine learning, analyzing
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programming (e.g., Python, MATLAB). Preferred Qualifications: Experience in resilience analysis for multi-agent systems. Familiarity with communication-constrained algorithm design. Prior work on communication
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closely with scholars in the humanities, historians, ethicists, legal scholars, and policy advocates. Within NetSI, our team collaborates with multiple research groups working on questions of public health
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machine learning methods in the context of biological systems Experience with programming (e.g., Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
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computer science, bioinformatics or related fields Solid understanding of machine and deep learning and relevant frameworks (e.g. Pytorch or Tensorflow, Keras, scikit-learn, OpenCV) Proficiency in Python, Linux and
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(or a related field), is proficient in both mechanistic modeling and ML frameworks (e.g., TensorFlow, PyTorch), and has strong programming skills (Python/MATLAB/C++). Join us to tackle sustainability
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(e.g. Matlab / Python) Experience of or willingness to work with pre-clinical tissue models (e.g. farmed meat) and human tissue (e.g. contaminated instruments in clinical facilities). A proven academic
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. Preferred Qualifications: Experience in machine learning, Python programming; first-principles studies of thermodynamics and defects in solids; experience in NEB calculations. Special Instructions
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open access of datasets. Key Responsibilities Develop and implement data management strategies to support research activities across multiple institutions. Collaborate with researchers to establish data
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that can process and learn from multiple data streams in real-time is key to unlocking the full potential of such instruments. The postdoctoral appointee will be responsible for developing such methods