Research Assistant Professor
CP11 University of New Hampshire
New Hampshire, United States2d ago
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About the role
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Summary
The Center for Coastal and Ocean Mapping (CCOM) at the University of New Hampshire (UNH) seeks an emerging researcher and educator for an Assistant Research Professor position. The successful candidate will hold a Ph.D. in Electrical and Computer Engineering, Mechanical Engineering, Computer Science, or a closely related field and will demonstrate expertise in programming, artificial intelligence, machine learning, remote sensing, signal processing, data analytics, and real-time or embedded systems.
The position will develop an externally funded research program focused on advanced computational methods for marine remote sensing and ocean mapping applications. The faculty member will conduct innovative research, contribute to and develop competitive proposals, participate in the management of grants and research projects, publish and present results, teach and contribute to curriculum development, mentor students and early-career researchers, and contribute expertise in artificial intelligence. The role includes designing and creating AI engines, supporting their responsible integration into research workflows, and participating in interdisciplinary AI working groups across CCOM, UNH, and partner organizations.
Duties/Responsibilities:
- Develop an independent program of research that applies artificial intelligence, machine learning, signal processing, remote sensing, and advanced data analytics to ocean mapping and marine sensing challenges.
- Design, develop, validate, and evaluate AI engines and machine learning models for real-time and post-processed interpretation, prediction, quality control, and decision support using seafloor acoustic and other marine remote sensing data.
- Develop methods and software tools for analyzing seafloor backscatter, sediment properties, environmental variability, and related oceanographic observations, including implementation in embedded or operational systems where appropriate.
- Contribute to interdisciplinary AI working groups by helping establish research priorities, coordinate technical activities, evaluate emerging methods, promote responsible and reproducible AI practices, and connect expertise across CCOM, UNH, government, academic, and industry partners.
- Identify funding opportunities and serve as principal investigator, co-principal investigator, or key personnel on competitive proposals to federal agencies, foundations, and industry sponsors; contribute to technical narratives, work plans, budgets, schedules, and collaborative agreements.
- Supervise research staff, graduate assistants, undergraduate researchers, and other project personnel as assigned; establish priorities, provide technical direction, and support professional development.
- Mentor graduate and undergraduate students in research design, computational methods, responsible AI, scientific writing, presentations, and career development; serve on graduate committees and advise student research as appropriate.
- Teach courses, seminars, workshops, or field and laboratory modules in areas such as artificial intelligence, machine learning, programming, signal processing, remote sensing, and marine data science; contribute to curriculum development and assessment.
- Produce peer-reviewed publications, technical reports, open and reproducible research products, conference papers, and presentations; communicate results to scientific, sponsor, operational, and public audiences.
- Develop collaborative relationships and represent CCOM and UNH at national and international meetings.
Minimum Qualifications:
- Ph.D. in Electrical and Computer Engineering, Mechanical Engineering, Computer Science, Data Science, Ocean Engineering, or a closely related field by the appointment start date.
- Demonstrated experience developing artificial intelligence or machine learning systems, including architecture, training, validation, deployment, or evaluation of research-grade AI engines.
- Demonstrated expertise in remote sensing, digital signal processing, data acquisition, data analytics, or real-time or embedded computing.
- Proficiency in two or more programming languages such as Python, C/C++, Go, and R, together with experience using modern machine learning frameworks, collaborative software development practices, and reproducible research workflows.
- Evidence of the ability to contribute to research proposals and externally funded projects, with potential to develop an independent sponsored research program.
- Experience teaching, mentoring students or early-career researchers, or supervising research activities.
- Evidence of scholarly productivity through peer-reviewed publications, conference presentations, technical reports, or other effective technical communication.
Preferred Qualifications:
- Experience developing scalable AI engines that integrate multimodal data, support real-time inference, or address model monitoring, uncertainty characterization, explain ability, and lifecycle management.
- Experience contributing to interdisciplinary technical teams, communities of practice, or AI working groups, including responsible-use guidance or shared research infrastructure.
- University-level teaching experience and experience supporting graduate student advising, thesis or dissertation committee service, or research staff supervision.
- Experience collaborating with federal agencies, academic institutions, or industry partners and translating research advances toward operational capabilities.
Applicant Instructions:
Applicants should be prepared to upload the following documents when applying online within the My Experience: Resume/CV section of the application:
(Maximum of 5 Documents - additional documents can be added to the Application Questions section of the application)
- Resume/CV
Applications that are missing any of the required items may not move forward for consideration. Additional uploaded documents not requested in the position announcement will not be reviewed.
Compensation Pay Range:
$75,000 for 9 month appointment
The rank of the selected candidate will depend upon the candidate’s qualifications.
Please be advised that this position is supported by external sponsor funding. As such, continued employment in this role is contingent upon the availability of those external funds. If, for any reason, the sponsor funding is reduced or discontinued, employment may be subject to modification or termination in accordance with applicable policies and procedures.
The University of New Hampshire is an R1 Carnegie classification research institution providing comprehensive, high-quality undergraduate and graduate programs of distinction. UNH is located in Durham on a 188-acre campus, 60 miles north of Boston and 8 miles from the Atlantic coast and is convenient to New Hampshire’s lakes and mountains. There is a student enrollment of 13,000 students, with a full-time faculty of over 600, offering 90 undergraduate and more than 70 graduate programs. The University actively promotes a dynamic learning environment in which qualified individuals of differing perspectives, life experiences, and cultural backgrounds pursue academic goals with mutual respect and shared inquiry.
EEO Statement
The University System of New Hampshire is an Equal Opportunity/Equal Access employer. The University System is committed to creating an environment that values and supports diversity and inclusiveness across our campus communities and encourages applications from qualified individuals who will help us achieve this mission. The University System prohibits discrimination on the basis of race, color, religion, sex, age, national origin, sexual orientation, gender identity or expression, disability, genetic information, veteran status, or marital status.
The pay range for this position is listed above. Actual offer will be based on skills, qualifications, experience, and internal equity, in addition to relevant business considerations. More information on benefits can be found here: USNH Employee Benefits | Human Resources
Location:
DurhamSalary Grade:
Faculty 01