Post-doctoral Associate

Description:

NYUAD is searching for a Post-Doctoral Associate to join the Transportation Infrastructure Management Lab (TIML), led by Prof. Samer Madanat. In particular, TIML seeks to welcome an enthusiastic and self-motivated scholar interested in the design and development of computationally efficient, data-driven methods for optimal planning and maintenance of highway infrastructure. The candidate must have a Ph.D. degree (or equivalent) in Engineering, Operations Research, Computer Science or related field and is expected to have a strong background and prior expertise in Deep Learning as well as Transportation Infrastructure in order to pursue multidisciplinary research at the intersection of these two realms.
 

• Understanding of transportation infrastructure systems maintenance and planning problems
• Advanced knowledge of methods of optimization under uncertainty, including Markov Decision Problems. Familiarity with MDP extensions (POMDP, Adaptive MDP, Approximate MDP) is an added advantage.
• Demonstrated research track record (with first author peer-reviewed publications ) in the areas of Machine Learning and Transportation Infrastructure.
• Solid experience and understanding of Deep Learning techniques.
• Expertise in advanced data analysis and interpretation techniques, including data pre-processing and preparation for machine learning models as well as experience in dealing with large datasets .
• Excellent oral and written communication skills
• Proven ability to work in a collaborative team environment, as well as independence and initiative.