117 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Ulster University" Postdoctoral positions at Cornell University in United States
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] Subject Areas: Physics / Hard Condensed Matter Theory , Machine Learning , Material Science , Physics , Quantum Information Science , Soft Condensed Matter Theory , theoretical condensed matter physics
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the lab. Hiring rate for this position is $64,723. To apply: Please apply via Academic Jobs Online https://academicjobsonline.org/ajo/jobs/30571 Qualified candidates should submit a short cover letter
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' professional position at the intersections of academic research, public engagement, and impact. Fellows are additionally supported by Cornell's Office of Postdoctoral Studies . Please visit https
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assistants and research technicians. Start date: Anticipated start of February 1, 2026. To apply: Please apply via Academic Jobs Online (https://academicjobsonline.org/ajo/jobs/30970 ). Qualified candidates
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. Supervision Exercised The individual is not expected to supervise others. To apply: Please apply via Academic Jobs Online https://academicjobsonline.org/ajo/jobs/30990 Qualified candidates should submit a short
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. Employee will have no supervisory responsibility To apply: Please apply via Academic Jobs Online https://academicjobsonline.org/ajo/jobs/30577 Qualified candidates should submit: a short cover letter
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: Please apply via Academic Jobs Online (https://academicjobsonline.org/ajo/jobs/29926 ), Qualified candidates should submit a short cover letter, curriculum vitae, contact information for three references
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machine learning approaches with large-scale biological data to automate genome curation by detecting, interpreting, and correcting structural errors, reducing manual effort from weeks to minutes thus
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work is studying how undergraduate STEM courses can be tailored to meet the needs of all learners. Current projects involve studying STEM instructor perceptions of student-centered learning as
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expertise in integrating advances in biomedical engineering, technology, and Artificial Intelligence (AI) and Machine Learning (ML) methods to tackle complex biomedical challenges in nutrition and health