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Machine Learning Model Development for Behavioral Prediction

Active
Federal

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

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This subcontract with the NASA Shared Services Center focuses on the development and training of machine learning models to predict team functioning for the NASA Human Research Program. The selected provider will be responsible for extracting linguistic markers and implementing both static and temporal models, specifically utilizing LSTMs and autoencoders. Technical execution requires proficiency in behavioral AI and temporal modeling, with development conducted using PyTorch or TensorFlow on high-performance computing resources. The primary deliverables for this engagement include pre-trained machine learning models and a fully documented software code repository hosted on GitHub. Based in Houston, the project falls under NAICS code 541511. Interested parties must adhere to the response deadline of September 22, 2026.

General Info

NASA subcontract for ML models predicting team functioning using behavioral AI and PyTorch.

Agency

National Aeronautics And Space Administration → NASA Shared Services CenterView Agency

NAICS

541511 - Custom Computer Programming ServicesView NAICS

Place of Performance

Houston, TX, 77058, USA

Set-Aside

NONE

Documents

This scope was carved out of 80NSSC26937562Q.

The full solicitation package (2 documents), including the RFP, is on the prime solicitation, not on this scope.

View the prime solicitation

AI system tailored to the Mars Exploration Analog

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Organization & Contact Information

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AgencyNational Aeronautics And Space Administration → NASA Shared Services Center
ContactsNo contacts available
OfficeN/A
Organization / Agency
National Aeronautics And Space Administration → NASA Shared Services Center
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Office AddressN/A
ContactsNo contact information available

Full Description

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Develops and trains AI models for prime contractors on NASA Human Research Program projects to predict team functioning. Extracts linguistic markers and trains static and temporal models, including LSTM and autoencoders, using PyTorch or TensorFlow on HPC resources. Requires proficiency in temporal modeling and behavioral AI. Delivers pre-trained ML models and a documented GitHub software code repository.

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