AST, Biological Studies (Direct Hire)

As an AI/ML (Artificial Intelligence/Machine Learning) Biological Scientist within the Space Biosciences Division, the incumbent leads development of advanced models, directs large scale scientific data analysis, guides interdisciplinary teams, and transitions validated AI/ML methods into operational tools. The position advances responsible AI, data governance, and innovation across NASA missions.

Major duties

• Lead the design, development, validation, and implementation of advanced AI/ML models to address complex scientific and biological research problems.
• Lead acquisition, integration, and analysis of complex datasets using ML and statistical methods for OSDR, PI for NASA EDGE bioinformatics, Team Lead for AI4LS, and Technical Lead for SMD Foundation Model.
• Advise managers, scientists, and interdisciplinary teams on model selection, experimental design, uncertainty, validation, and appropriate interpretation of AI-generated results.
• Lead multidisciplinary research projects involving AI/ML, establish research objectives and methodologies, evaluate emerging technologies, and coordinate project activities with internal programs, universities, industry, and other Federal partners.
• Lead the transition of validated AI/ML methods from research into operational tools, decision-support systems, and scientific workflows; establish standards for model performance, reproducibility, documentation, data governance.

Qualifications

In addition to the Basic Education Requirement (in the Education section below), to qualify for this position you must meet the requirements below. Specialized experience is experience that has equipped you with the particular ability, skill, and knowledge to successfully perform the duties of this position and is typically in or related to this line of work. NASA utilizes OPM-approved qualification and rating requirements specific for Aerospace Technology (AST) positions which recognizes NASA's unique aerospace work. The specific qualifications and minimum education requirements are further described below and within the education section of the job announcement. To qualify for GS-13, you must have one year of directly related specialized experience equivalent to the GS-12 level: Contributing to the development, evaluation, and application of advanced artificial intelligence and machine learning models to solve scientific and biological problems, including selecting appropriate algorithms, designing experiments, validating model performance, and interpreting results; Collaborating with multidisciplinary research projects involving large and complex scientific datasets, including data acquisition, integration, statistical analysis, machine learning, and development of reproducible computational workflows; Providing input on artificial intelligence and machine learning applications in a scientific environment, translating research into operational decision-support tools, evaluating emerging technologies, and establishing standards for model validation, uncertainty, reproducibility, and responsible AI implementation. Your resume must include a clear and detailed narrative description, in your own words, of how you meet the required specialized experience. Experience statements copied from a position description, vacancy announcement or other reference material constitutes plagiarism and may result in disqualification and losing consideration for the job. Please visit https://www.nasa.gov/careers/how-to-apply/#Artificial-Intelligence to review NASA's guidance on the use of artificial intelligent (AI) or AI-assisted tools during the application process.

Education

This position requires education or exceptional experience. Basic Education Requirement: You must have successfully completed a bachelor's degree with a major in one of the following: a) Engineering from a college or university that has ABET accredited engineering programs b) Physical Science, Mathematics, Life Science or other field of Science c) Computer Science that included 30 semester hours or 45 quarter hours of course work in any combination of mathematics, statistics and computer science with at least half of those hours in mathematics and statistics courses that included differential and integral calculus; and that provided an in-depth knowledge of theoretical and practical applications of computer science, including digital computer system architecture and system software organization, the representation and transformation of information structures, and the theoretical models for such representations and transformations. If you did not complete a qualifying bachelor's degree, you may be eligible if you have obtained a graduate degree in an AST qualifying field, as listed above. Applicants who do not fully meet the basic education requirement may still be considered if they possess exceptional relevant experience, or a combination of education and experience, that clearly demonstrates significant full performance-level achievement directly related to the duties of this position. Engineering degrees earned within the United States: Engineering degrees earned within the United States must be from a college or university that has at least one ABET accredited engineering program. To find out if a school has at least one ABET accredited program, please visit http://www.abet.org. Engineering degrees earned outside the United States: Engineering degrees earned outside the United States must be recognized by a Mutual Recognition Agreement (MRA), often known as accords. These are non-governmental agreements among organizations that accredit academic degree programs. MRAs recognize the substantial equivalence of mature accreditation systems and programs accredited by signatory organizations within their jurisdictions. For a listing of Signatories, please visit, https://www.abet.org/global-presence/mutual-recognition-agreements/is-your-program-recognized/. Science and other related degrees earned within the United States: Science and other related degrees must have been awarded from colleges or universities that are accredited by recognized accrediting organizations. For a list of schools that meet this criteria, go to http://ope.ed.gov/accreditation/. Science and other related degrees earned outside the United States: If you are using education completed in foreign colleges or universities to meet the qualification requirements, you must show that the education credentials have been evaluated by a private organization that specializes in interpretation of foreign education programs. These education credentials must be deemed equivalent to that gained in an accredited U.S. education program; or full credit has been given for the courses at a U.S. accredited college or university. For further information, visit: https://sites.ed.gov/international/recognition-of-foreign-qualifications/. All degrees must have been received in the year of, or any year subsequent to the original date of accreditation.