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experience with management and strategy research, economic modelling and statistical analyses are essential. Familiarity with data mining, machine learning and computation techniques, especially in the context
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by ARPES, pursue scalable wafer-scale moiré epitaxy, develop epitaxial superconductors for quantum computing and integrate machine learning for automated high-throughput MBE. We are particularly
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. Experience in, or willingness to learn data-driven approaches, including artificial intelligence (AI) and machine learning (ML) models, to solve problems. The Successful Candidate Will A curious scholar with a
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Computer Science, Artificial Intelligence, Software Engineering, or a related field. Strong programming proficiency in Python and/or C++. Demonstrable experience with machine learning frameworks (e.g., PyTorch
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in Spatial Omics and Multi-Modal Data Integration Duties & Responsibilities: Develop computational and machine learning methods for spatial omics data (spatial transcriptomics, spatial proteomics
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qualifications: Experience with implementation or applications of large machine learning models Experience with generative methods for protein design and/or docking simulations or generative methods
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or Machine Learning). The master thesis must be included in the application. Documented proficiency in English, please see requirements below. Requirements for proficiency in English This position requires
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, Mathematics (Operations research) or Computer Science or Machine Learning). The master thesis must be included in the application. Documented proficiency in English, please see requirements below. Requirements
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | 19 days ago
miscategorization of subjects with potential DILI risk during regulatory review. Through this opportunity, you will cooperate in research and training activities related to computer modeling and statistical analyses
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(kidney biopsy, serum, urine) for comprehensive biomarker profiling. Utilization of machine learning and image processing for advanced tissue analysis. The Herman B Wells Center for Pediatric Research