Astrophysicist, AI (Postdoctoral Research Fellow) (IS-1330-11) - Smithsonian Astrophysical Observatory
Cambridge, MA
About the Job
Description
OPENING DATE: October 23, 2024
CLOSING DATE: November 22, 2024
TYPE OF POSITION: Trust Indefinite (Non-Federal)
DIVISION: Office of Director
LOCATION: Cambridge, MA
AREA OF CONSIDERATION: This position is open to all eligible candidates.
CLOSING DATE: November 22, 2024
TYPE OF POSITION: Trust Indefinite (Non-Federal)
DIVISION: Office of Director
LOCATION: Cambridge, MA
AREA OF CONSIDERATION: This position is open to all eligible candidates.
What are Trust Fund Positions?
Trust Fund positions are unique to the Smithsonian. They are paid for from a variety of sources, including the Smithsonian endowment, revenue from our business activities, donations, grants and contracts. Trust employees are not part of the civil service, nor does trust fund employment lead to Federal status. The salary ranges for trust positions are generally the same as for federal positions and in many cases trust and federal employees work side by side. Trust employees have their own benefit program, which may include Health, Dental & Vision Insurance, Life Insurance, Transit/Commuter Benefits, Accidental Death and Dismemberment Insurance, Annual and Sick Leave, Family Friendly Leave, 403b Retirement Plan, Discounts for Smithsonian Memberships, Museum Stores and Restaurants, Credit Union, Smithsonian Early Enrichment Center (Childcare), Flexible Spending Account (Health & Dependent Care).
Conditions of Employment
- Pass Pre-employment Background Check and Subsequent Background Investigation, as required.
- Complete a Probationary Period if applicable.
- Maintain a Bank Account for Direct Deposit/Electronic Transfer.
- The position is open to all candidates eligible to work in the United States. Proof of eligibility to work in U.S. is not required to apply.
- Applicants must meet all qualification and eligibility requirements within 30 days of the closing date of this announcement.
OVERVIEW
INTRODUCTION
The Smithsonian Astrophysical Observatory (SAO) is at the forefront, internationally, of the scientific exploration of the universe. SAO combines its resources with those of the Harvard College Observatory to form the Harvard-Smithsonian Center for Astrophysics (CfA). The CfA is the best-known astrophysics center in the world. Its programs range from ground-based astronomy and astrophysics research to space-based research, the engineering and development of major scientific instrumentation for space launch and use in large ground-based facilities, and research designed to improve science education. The research objectives of SAO are carried out primarily with the support of Government and Smithsonian Institution funds, with additional philanthropic support. Government funds are in the form of Federal appropriations or the form of contracts and grants from other agencies. In contrast, Institution funds are available to SAO through grants from the Institution's Restricted Funds, Special Purpose Funds, Bureau Activities, Business Activities, and non-Federal contracts and grants.
SUMMARY
The purpose of this position is to participate in the development of methods to leverage Large Language Models (LLMs) to enhance scientific research and to combine them with representation learning methods for astronomical data (images, spectra, light curves, X-ray event files), to extract meaningful correlations between astronomical literature and astronomical data, through the use of contrastive learning approaches. The candidate will join a team of multidisciplinary researchers, including astronomers, natural language processing experts, and computer scientists working at the intersection between astronomy and artificial intelligence.
The Smithsonian Astrophysical Observatory (SAO) is at the forefront, internationally, of the scientific exploration of the universe. SAO combines its resources with those of the Harvard College Observatory to form the Harvard-Smithsonian Center for Astrophysics (CfA). The CfA is the best-known astrophysics center in the world. Its programs range from ground-based astronomy and astrophysics research to space-based research, the engineering and development of major scientific instrumentation for space launch and use in large ground-based facilities, and research designed to improve science education. The research objectives of SAO are carried out primarily with the support of Government and Smithsonian Institution funds, with additional philanthropic support. Government funds are in the form of Federal appropriations or the form of contracts and grants from other agencies. In contrast, Institution funds are available to SAO through grants from the Institution's Restricted Funds, Special Purpose Funds, Bureau Activities, Business Activities, and non-Federal contracts and grants.
SUMMARY
The purpose of this position is to participate in the development of methods to leverage Large Language Models (LLMs) to enhance scientific research and to combine them with representation learning methods for astronomical data (images, spectra, light curves, X-ray event files), to extract meaningful correlations between astronomical literature and astronomical data, through the use of contrastive learning approaches. The candidate will join a team of multidisciplinary researchers, including astronomers, natural language processing experts, and computer scientists working at the intersection between astronomy and artificial intelligence.
MAJOR DUTIES
- Conduct scientific research in fields of generative artificial intelligence, including large language models, representation learning, variational inference, and contrastive learning, collaborating with a multi-disciplinary team of researchers, including astronomers, computer scientists, and software engineers.
- Contribute to the compilation of a multi-modal dataset for the purpose of self-supervised learning, including data from the Chandra X-ray observatory, NASA’s Astrophysics Data System, and other optical and infrared surveys
- Formulate new approaches for the training of deep neural networks (transformers, variational auto-encoders, etc.) to create low-dimensional representations, and use the resulting representations for a set of downstream tasks including regression, classification, and contrastive learning.
- Interact with Natural language Processing experts to incorporate knowledge for NLP in the task of defining strategies to extract meaningful semantic representations from astronomical literature.
- Stay up to date with the latest publications in the fields of large language models for science, contrastive learning, self-supervised learning, and methods of variational inference.
- Mentor and assist graduate students as appropriate and as directed to achieve the project's goals.
- Participate in meetings and conferences to discuss current research and to exchange data and ideas with other scientists.
QUALIFICATION REQUIREMENTS
Basic Requirements:
A. Degree: in one or a combination of astronomy, physics, mathematics, space science, or electronics. The coursework must include differential and integral calculus and 12 semester hours in astronomy and/or physics.
OR
B. Combination of education and experience -- at least 30 semester hours of courses equivalent to a major in any combination of astronomy, space science, physics, mathematics, and electronics, with required course work as shown in A above, plus appropriate experience or additional education.
OR
B. Combination of education and experience -- at least 30 semester hours of courses equivalent to a major in any combination of astronomy, space science, physics, mathematics, and electronics, with required course work as shown in A above, plus appropriate experience or additional education.
In addition to the basic requirements, candidates for the grade 11 must also possess one of the following:
A. Master's or equivalent graduate degree; or
B. Minimum of one year of specialized experience equivalent to at least grade 9 in the normal line of progression for this occupation. Specialized experience is experience that has equipped the applicant with the particular competencies/knowledge, skills, and abilities to successfully perform the duties of the position such as processing scientific data, conducting research, and publishing scientific journal articles.
A. Master's or equivalent graduate degree; or
B. Minimum of one year of specialized experience equivalent to at least grade 9 in the normal line of progression for this occupation. Specialized experience is experience that has equipped the applicant with the particular competencies/knowledge, skills, and abilities to successfully perform the duties of the position such as processing scientific data, conducting research, and publishing scientific journal articles.
C. Combination of successfully completed graduate-level education and experience equivalent to the above.
Knowledge, Skills, and Abilities required:
- Ability to perform scientific research as evidenced by receipt of a Ph.D in astrophysics, computer science, or related field.
- Knowledge of machine learning
- Knowledge of python programming for machine learning: pytorch or tensorflow
- Skill in developing new software and modifying existing programs
- Ability to present findings in a publishable format
- Skill in oral and written communication as evidenced by refereed journal publications in
- molecular spectroscopy and relevant applications
Education completed outside the United States must be deemed equivalent to higher education programs of U.S. Institutions by an organization that specializes in the interpretation of foreign educational credentials. This documentation is the responsibility of the applicant and should be included as part of your application package.
Any false statement in your application may result in rejection of your application and may also result in termination after employment begins.
The Smithsonian Institution values and seeks a diverse workforce. Join us in "Inspiring Generations through Knowledge and Discovery."
Resumes should include a description of your paid and non-paid work experience that is related to this job; starting and ending dates of job (month and year); and average number of hours worked per week.
What To Expect Next: Once the vacancy announcement closes, a review of your resume will be compared against the qualifications and experience requirements related to this job. After review of applicant resumes is complete, qualified candidates will be referred to the hiring manager.
Relocation expenses are not paid.
Commitment to Diversity, Equity, and Inclusion
The Smithsonian Institution provides reasonable accommodation to applicants with disabilities where appropriate. Applicants requiring reasonable accommodation should contact hr@cfa.harvard.edu. Determinations on requests for reasonable accommodation will be made on a case-by-case basis. To learn more, please review the Smithsonian’s Accommodation Procedures.
Commitment to Diversity, Equity, and Inclusion
The Smithsonian Institution provides reasonable accommodation to applicants with disabilities where appropriate. Applicants requiring reasonable accommodation should contact hr@cfa.harvard.edu. Determinations on requests for reasonable accommodation will be made on a case-by-case basis. To learn more, please review the Smithsonian’s Accommodation Procedures.
The Smithsonian Institution is an Equal Opportunity Employer. We believe that a workforce comprising a variety of educational, cultural, and experiential backgrounds support and enhance our daily work life and contribute to the richness of our exhibitions and programs. See Smithsonian EEO program information: https://www.si.edu/oeesd.
The Smithsonian Astrophysical Observatory is an equal opportunity employer committed to diversity in our workplace. Please visit the SAO website at http://www.cfa.harvard.edu/
Source : Smithsonian Astrophysical Observatory
