2027 PhD Graduate – Health Systems Engineer / Analyst

Johns Hopkins Applied Physics Laboratory•Laurel, MD

About The Position

The Health and Human-Machine Systems Group seeks a PhD graduate to help design and operationalize advanced and autonomous solutions for complex socio-technical systems. The role applies engineering, computer science, data science, advanced analytics, artificial intelligence and machine learning, and cognitive and behavioral sciences to challenges involving the integration of systems, humans, and operations. Work is performed in collaboration with government, academia, and industry, supporting the Nation and its warfighters. As part of a multidisciplinary team, you will investigate, evaluate, analyze, and prototype technologies and operational solutions, potentially developing system concepts and technologies for autonomous or intelligent health and human-machine partnerships. You will work with operational stakeholders to understand and document needs and translate them into requirements that support analysis, modeling and simulation, and system design. The position also supports design and peer reviews, documentation and presentation of work products, and potentially quantitative social science research. You will help define new approaches to operational challenges and build cross-organizational relationships.

Requirements

Possess a PhD in engineering, computer science, mathematics, or computational social science.
Demonstrate application of expertise to human-machine teaming or socio-technical challenges.
Be able to manage multiple simultaneous assignments and priorities.
Have excellent interpersonal, written, and verbal communication skills and demonstrated success working in a team environment.
Be able to travel occasionally for meetings with government sponsors and operational stakeholders.
Be able to obtain an Interim Secret security clearance by the start date and ultimately obtain a Secret clearance; eligibility requires U.S. citizenship.

Nice To Haves

Demonstrable experience with data analysis or modeling and simulation tools such as Python, Matlab, Advanced Excel (VBA), R, Simio, or MagicDraw.
Experience with Model-Based Systems Engineering (MBSE) and systems modeling concepts, including block and context diagrams, requirements management, and activity and process diagrams.
Ability to research and quickly identify industry design trends and user interface best practices to achieve a positive user experience.
Demonstrated interest in human-machine teaming challenges.
Experience understanding and interpreting physiological data.
Experience assessing and measuring human performance and applying AI/ML capabilities to improve human-machine teaming and autonomous systems interfaces.

Responsibilities

Investigate, evaluate, analyze, and prototype technologies and operational solutions as part of a multidisciplinary team.
Develop system concepts and technologies to mature autonomous or intelligent health and human-machine partnerships.
Collaborate with operational stakeholders to understand and document needs and translate them into well-defined requirements for analysis, modeling and simulation, or system design.
Support design and peer reviews covering analytical approaches, techniques, system design, integration, and testing methodologies.
Revise, document, and present work products based on review feedback and APL quality standards.
Potentially conduct quantitative social science research through observational and experimental studies, including multi-factor modeling, social media analysis, time series analysis, and natural language processing.
Define innovative approaches to operational challenges and establish cross-organizational relationships to increase collaboration.