Multi-modal Sensing and Human-Machine Integration for Adaptive AI in Tactical Environments

About the role

We are seeking a postdoctoral research fellow to investigate multi-modal sensor-fusion approaches for understanding human behavior in realistic environments to facilitate human-AI adaptation at the tactical edge. The goal is to leverage advanced analytics on human-derived signals from diverse systems to passively predict actions and estimate user state, enabling future AI platforms for dismounted Soldiers to quickly adapt to changing needs.

Responsibilities

• Conduct research to understand the relationship between critical behaviors and relevant data/metrics from wearables (physiological and biomechanical), AR/VR systems, and other off-body systems.
• Participate in multi-disciplinary teams consisting of cognitive psychologists, neuroscientists, engineers, and data scientists.
• Contribute to research and/or work experience at the intersection of wearables, bio-signals, machine learning, and individual and team performance outcomes.
• Knowledge of advanced machine learning techniques such as reinforcement learning is a plus.

Requirements

• Ph.D. in a relevant field (e.g., computer science, engineering, psychology, neuroscience).
• Experience with multi-modal sensor fusion and human-machine interaction.
• Strong background in machine learning and data analysis.
• Ability to work in a collaborative environment with interdisciplinary teams.

Qualifications

• Research and/or work experience at the intersection of wearables, bio-signals, machine learning, and individual and team performance outcomes.
• Advanced knowledge of machine learning techniques, particularly reinforcement learning.
• Experience with human-computer interaction and human factors research.

Skills

• Expertise in multi-modal sensor fusion and data analysis.
• Proficiency in machine learning algorithms and techniques.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills.

Benefits

• Opportunity to contribute to cutting-edge research in the field of human-AI integration.
• Collaboration with a multidisciplinary team of experts.
• Access to state-of-the-art facilities and resources.

Pay

• Salary range: $50,000 - $60,000 per year, depending on experience and qualifications.

Schedule

• Full-time position.

About ARL

The Army Research Laboratory (ARL) is dedicated to exploring and developing innovative science and technology to meet the Army's future needs. ARL's Army Research Directorate (ARD) focuses on leveraging concept development, discovery, technology development, and transition to deliver fundamental advantages in science-based capabilities through laboratory's 11 research competencies. ARL-RAP is designed to significantly increase the involvement of creative and highly trained scientists and engineers from academia and industry in scientific and technical areas of interest and relevance to the Army.

About ARL-RAP

The Army Research Laboratory Research Associateship Program (ARL-RAP) aims to engage and involve creative and highly trained scientists and engineers from academia and industry in scientific and technical areas of interest and relevance to the Army. Scientists and Engineers at ARL help shape and execute the Army's program for meeting the challenge of developing technologies that will support Army forces in meeting future operational needs by pursuing scientific research and technological developments in diverse fields such as applied mathematics, atmospheric characterization, simulation and human modeling, digital/optical signal processing, nanotechnology, material science and technology, multifunctional technology, combustion processes, propulsion and flight physics, communication and networking, and computational and information sciences.

About HCxS

HUMANS IN COMPLEX SYSTEMS (HCxS) focuses on non-medical approaches to understand and modify the potential of humans situated in and interacting within complex social, technological, and socio-technical systems.

A complete application includes:

• Curriculum Vitae or Resume
• Three References Forms
• Transcripts

Contact Information

If selected by an advisor, the participant will be required to write a research proposal to submit to the ARL-RAP review panel. Questions about this opportunity can be emailed to ARLFellowship@orau.org.

Qualifications

• Citizenship: U.S. Citizen Only
• Degree: Master's Degree or Doctoral Degree
• Academic Level(s): Any academic level
• Discipline(s): Relevant fields such as computer science, engineering, psychology, neuroscience

ORAU Opportunities

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