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related subject, or be close to completing their qualification. They should have experience in systems engineering, simulation, digital modelling, machine learning, artificial intelligence, or digital twin
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that delivers real-time, hyperlocal information on urban heat risks in tropical cities. Leveraging Doppler lidar–based microclimate studies and machine learning, the research emphasizes vulnerable groups
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, United States of America [map ] Subject Areas: Electrical and Computer Engineering / artificial intelligence , Artificial Intelligence and Machine Learning (AI/ML) Starting Date: 2026/01/01 Salary Range: $62,232-$80,000
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bioinformatics analysis. Learning Objectives: You will receive training in handling various viruses and gain experience in different sample processing procedures to extract nucleic acids for NGS and learning
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. Learning Objectives: Under the guidance of a mentor, you will engage in learning research focused on understanding antibody responses to conserved and variable epitopes in rapidly evolving RNA viruses, with
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including spectral flow cytometry, machine learning and irradiation techniques to generate bone marrow chimera models. Utilize mouse models and patient-derived samples to explore how biological immune aging
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work on a project to conduct research on learning from human demonstrations for robot manipulation used in household service and manufacturing. The roles of this position include: Develop robotic
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 24 hours ago
will have the opportunity to disseminate research findings to internal and external data stakeholders (e.g. publication) Learning Objectives: Under the guidance of a mentor, you will: Develop useful
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of research, testing and data collection, analysis and evaluation, and writing reports which contain descriptive, analytical and evaluative content. The purpose of this role is to acquire the professional
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JavaScript code using contrastive learning with a tailored security-aware loss function. The student will fine-tune selected models using secure-insecure code pairs derived from Tasks 1 and 2 and evaluate