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Field
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date is 1 Januar 2026, with room for flexibility in both directions. We are seeking a highly motivated individual with a PhD in computer science, computational chemistry / biochemistry, applied
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Python, TensorFlow, PyTorch, or similar frameworks. MS or higher degree (PhD preferred) degree in Computational Neuroscience, Computer Science, Bioinformatics, or a related field with demonstrated ability
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Qualifications PhD in Neuroscience or related field (summer and fall graduates are also welcome to apply). Strong knowledge and experience with patch-clamp electrophysiology. The ability to perform patch-clamp
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preliminary analysis of the data using graphs, charts or tables to highlight the key points of the research results collected in accordance with the research protocols as stipulated. Prepare and present
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using graphs, charts or tables to highlight the key points of the research results collected in accordance with the research protocols as stipulated. Proofread and edit research data and documents
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knowledge graphs and multimodal embeddings for cancer patient digital twin construction. Lead and co-author high-impact publications and grant proposals. Collaborate with clinicians, bioinformaticians, and
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Physics, Spectral Theory, Quantum Chaos, Large Graphs and Quantum Walks. Related areas such as Quantum Information can also be considered. This position is offered through the research funds of Mostafa
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in the following areas: Deep Learning, Scientific Machine Learning, Stochastjc Gradiant Descent Method, and Numerical PDE’s - Advised by Dr. Yanzhao Cao Probabilistic Graph Theory (Network Traversal
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initial interpretations to guide research efforts. Prepare visual aids such as charts, graphs, and illustrations to effectively communicate research results. Perform thorough literature reviews to stay
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knowledge graphs, rules, and process understanding, with implications across sectors from ecology to infrastructure. 4. Theme 4 (“Communities”): Green and Resilient Communities and Entrepreneurship