29 parallel-computing "Constructor Labs" Postdoctoral positions in United Arab Emirates
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guidance of two experts in computational microscopy and machine learning systems, blending expertise in advanced bioimage informatics and parallel computing: Dr. Min Xu – Affiliated Associate Professor
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Computing and Mathematical Sciences Division - Postdoctoral Researcher: Statistics and Machine Learn
data. Manage preferences for further information and to change your choices. Accept all cookies Reject optional cookies Skip to main content Computing and Mathematical Sciences Division
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data. Manage preferences for further information and to change your choices. Accept all cookies Reject optional cookies Skip to main content Computing and Mathematical Sciences Division
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, statistics, machine learning, programming in C, C++, Python Scripting languages and MATLAB, using a parallel computing environment Bioinformatics, network biology, network medicine, network analytics, AI, ML
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students in mathematics, scientific computing, data science, biology, and biomedical applications. The successful applicant will be encouraged to participate actively in seminars, workshops, and
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solid experience in practical AI/ML system development. Additional knowledge on MLOps, robust/secure computing, Hallucinations and Alignment, privacy-preserving ML, and ML security is highly desirable
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research at the intersection of computing and healthcare. Methodologies of interest include: multi-modal learning, foundation models, including large language models, agentic AI, multi-agent AI
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research at the intersection of computing and healthcare. Methodologies of interest include: multi-modal learning, foundation models, including large language models, agentic AI, multi-agent AI
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solid experience in practical AI/ML system development. Additional knowledge on MLOps, robust/secure computing, Hallucinations and Alignment, privacy-preserving ML, and ML security is highly desirable
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research at the intersection of computing and healthcare. Methodologies of interest include: multi-modal learning, foundation models, including large language models, agentic AI, multi-agent AI