Postdoctoral Research Fellow

About the Opportunity

Northeastern University is looking for a postdoctoral research fellow in artificial intelligence (AI) and machine learning (ML) as well as network science (NS) and optimization (NO) for threat deterrence, risk assessment, and resource allocation in the broad area of transportation security. An earned PhD in computer science or transportation engineering or related areas, or at least an all-but-dissertation status, is required prior to the start date. The applicant must have demonstrated interest in both transportation and data-driven sciences. Prior work or demonstrated interest in weather and climate hazards, as well as in cyber and physical threats,

especially in the context of surface transportation and urban systems, is a plus. The selected applicant will work under the mentorship of Professor Auroop Ganguly at Northeastern University (NU) in Boston, MA, who has a joint appointment as a chief scientist at the US DOE’s Pacific Northwest National Laboratory (PNNL) in Richland, WA, and the co-mentorship of Dr. Samrat Chatterjee, who is a chief data scientist at PNNL and an affiliate professor at NU. The selected applicant will have an opportunity to contribute significantly to a NU-led Department of

Homeland Security (DHS) Center of Excellence (COE) called SENTRY (Soft Target Engineering to Neutralize the Threat Reality).

Research Description:

Emerging AI and ML methods, combined with NS/NO approaches and graphical ML, are becoming increasingly critical in diverse infrastructure security domains. We are looking for postdoctoral candidates with strong AI/ML background applied to transportation infrastructure security spaces. Candidates will work in the areas of graph neural networks, network simulation modeling, and risk and decision analytics with applications to surface transportation systems.

Qualifications:

To contribute to these research efforts, a successful candidate will have an earned PhD and technical expertise in one or more areas including deep learning, network and decision science, transportation engineering, optimization, risk analysis, and uncertainty quantification. In addition, the candidate should be proficient in latest programming languages and software tools for machine learning and optimization. The candidate is expected to collaborate effectively within multi-disciplinary research teams at NU (Boston, MA, and Portland, ME) and PNNL (Richland, WA, and Seattle, WA).

Position Type

Research

Additional Information

Northeastern University considers factors such as candidate work experience, education and skills when extending an offer.  

Northeastern has a comprehensive benefits package for benefit eligible employees. This includes medical, vision, dental, paid time off, tuition assistance, wellness & life, retirement- as well as commuting & transportation. Visit https://hr.northeastern.edu/benefits/ for more information.  

Northeastern University is an equal opportunity employer, seeking to recruit and support a broadly diverse community of faculty and staff.  Northeastern values and celebrates diversity in all its forms and strives to foster an inclusive culture built on respect that affirms inter-group relations and builds cohesion. 

All qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, religion, color, national origin, age, sex, sexual orientation, disability status, or any other  characteristic protected by applicable law.

To learn more about Northeastern University’s commitment and support of diversity and inclusion, please see www.northeastern.edu/diversity .