9 дней назад
PostDoc – Machine Learning (AI)
74 050 - 122 550$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
PostDoc – Machine Learning (AI): Conducting basic and applied machine learning research for autonomous scientific discovery and DOE security problems with an accent on multimodal foundation models, continuous learning, and agentic AI systems. Focus on developing and adapting models, building large-scale learning systems, analyzing multimodal data, and collaborating with interdisciplinary scientific experts.
Location: Fully onsite at in Upton, New York, United States
Salary: $74,050–$122,550 per year
Company
is a multidisciplinary U.S. Department of Energy laboratory focused on discovery science and transformative technology.
What you will do
- Conduct basic and applied machine learning research for scientific and security problems.
- Develop novel machine learning models and adapt existing approaches for scientific applications.
- Research multimodal foundation models, continuous learning, and agentic AI systems for autonomous discovery, planning, and decision-making.
- Collaborate with subject matter experts on scientific data generation, processing, and method evaluation.
- Formulate research directions with mentors and communicate progress, challenges, and results.
Requirements
- Ph.D. in computer science or a related field, received by the employment start date.
- Strong theoretical and practical experience in machine learning, multimodal foundation models, continuous learning, and agentic AI.
- Demonstrated publication record in machine learning.
- Excellent programming and computer science skills.
- Ability to work fully onsite at the BNL facility in Upton, New York.
- Relevant postdoctoral and R&D experience after the Ph.D. must not exceed five combined years, subject to stated exclusions.
Nice to have
- Experience developing novel machine learning, multimodal foundation model, continuous learning, or agentic AI systems.
- Experience with state-of-the-art multimodal foundation models and agentic AI frameworks.
- Experience with large-scale deep learning, foundation model training or fine-tuning, and continuous learning pipelines.
- Experience analyzing image, video, and text data.
- Experience in multidisciplinary collaborations.
Culture & Benefits
- Access to the BNL Institutional Cluster and DOE leadership computing facilities for large-scale computation.
- Access to unique scientific data sources and interdisciplinary research programs.
- Initial two-year appointment, renewable based on performance and funding.
- Comprehensive employee benefits program.
- REAL-ID-compliant identification is required for access to the federal laboratory site, including interviews.
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