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Postdoctoral Researcher, Trustworthy ML (PhD)
MetaNew York City, United Statesfull_timeVerifiedPosted 27 Apr 2024
About the role
Meta is seeking a Postdoctoral Researcher to join Fundamental AI Research (FAIR), a research organization focused on making significant progress in AI. Individuals in this role are expected to be recognized experts in identified research areas such as artificial intelligence and machine learning.
In particular, we are looking for candidates interested in exploring the impact of data curation on privacy, fairness, and robustness as well as other topics in privacy and security of large-scale multi-modal models. Potential research directions may investigate whether data curation has disparate impacts across groups, how data design impacts the ability of adversaries to compromise privacy, whether data choices can improve fairness, or other directions related to these topics. Projects will be determined together with the Postdoc, supervisor, and other researchers in FAIR.
We are seeking candidates with a keen interest in developing novel approaches that lead to better solutions for core machine learning problems, with a focus on trustworthy aspects of machine learning, such as privacy, fairness and robustness.
Postdoc positions are one to two year fixed-term positions.Postdoctoral Researcher, Trustworthy ML (PhD) Responsibilities
Individual pay is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base salary, Meta offers benefits. Learn more about benefit
In particular, we are looking for candidates interested in exploring the impact of data curation on privacy, fairness, and robustness as well as other topics in privacy and security of large-scale multi-modal models. Potential research directions may investigate whether data curation has disparate impacts across groups, how data design impacts the ability of adversaries to compromise privacy, whether data choices can improve fairness, or other directions related to these topics. Projects will be determined together with the Postdoc, supervisor, and other researchers in FAIR.
We are seeking candidates with a keen interest in developing novel approaches that lead to better solutions for core machine learning problems, with a focus on trustworthy aspects of machine learning, such as privacy, fairness and robustness.
Postdoc positions are one to two year fixed-term positions.Postdoctoral Researcher, Trustworthy ML (PhD) Responsibilities
- Engage with the supervisor and other researchers in Fundamental AI Research (FAIR) to develop and implement research agenda, publish world-class research works, and make external impact.
- Identify highly impactful projects in a complex and unexplored domain.
- Currently has or is in the process of obtaining a PhD degree in the field of Artificial Intelligence, Machine Learning, Operation Research or a related field, or equivalent practical experience. Degree must be completed prior to joining Meta
- Experience in learning frameworks (such as PyTorch, TensorFlow), C, C++, Python.
- Basic research experience with publications in conferences/journals in the related fields.
- Have basic research experience with publications in conferences/journals in the related fields
- Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.
- Publication record in Machine learning or related area.
- Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops, journals or conferences in Machine Learning (NeurIPS, ICML, ICLR). Other closely related track records (e.g., Operation Research, MLSys) will also be considered in a case-by-case manner.
- Demonstrated research and software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
- Experience with manipulating and analyzing complex, large scale, high-dimensionality data from varying sources.
- Experience solving complex problems and comparing alternative solutions, trade-offs, and diverse points of view to determine a path forward.
- Prior experience working with multimodal models or on privacy and fairness.
Individual pay is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base salary, Meta offers benefits. Learn more about benefit
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