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The Wee Kim Wee School of Communication and Information (WKWSCI), together with the Earth Observatory of Singapore, is looking for a Research Fellow to make an important contribution to the research
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USDA-ARS Molecular Biology Postdoctoral Fellowship in the Natural Products Utilization Research Unit
interactions. These directives require a multifaceted approach involving physiological, biochemical, and molecular experiments and the use of numerous techniques such as RNA-seq, data mining of DNA and protein
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graph construction and mining, CDE development for data harmonization. Regulatory science and explainable AI, verification, validation, uncertainty quantification, and AI evaluation framework High
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uncertainty. Utilize machine-learning and data-mining approaches to recommend bioengineering interventions. Develop new machine-learning algorithms. Integrate machine learning techniques with mechanistic
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by Jul 27, 2026: The University of Notre Dame invites applications for a Postdoctoral Research Fellow with deep expertise in quantitative data analysis, data science, and artificial intelligence (AI
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discovery by performing gene mining, constructing and screening transporter libraries, engineering microbial hosts, and analyzing pooled sequencing data to identify transporter function. Interpret and present
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. Apply the platform to large-scale transporter discovery by performing gene mining, constructing and screening transporter libraries, engineering microbial hosts, and analyzing pooled sequencing data
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intricate. Specializing in program analysis and software analytics, the lab works on enhancing the precision and scalability of static analyses and mining insights from software repositories. Ongoing research
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School of Mechanical and Mining Engineering, Faculty of EAIT Full-time (100%), fixed-term position for up to 12 months Academic Level A or B (Postdoctoral Research Fellow / Research Fellow) Level A
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in educational data mining and AI for education, with the ability to handle a large amount of data Prior experience working with LLMs, including programming, fine-tuning, evaluating and benchmarking