Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
emphasis on applied machine learning, artificial intelligence and experiential network addressing the business challenges in the industry. Instructional areas include, but are not limited to, analytics, with
-
interested in applicants who use advanced quantitative methods, including computational modeling, machine learning, and/or analyzing structural and functional neuroimaging data. Specific activities may include
-
and methodological perspective of an engineer. Students build advanced design and engineering skills, enhance their knowledge in cloud computing, and develop machine learning algorithms. With a passion
-
About the Opportunity About this opportunity: Northeastern University is a global leader in experiential learning and cooperative education in which students alternate between academic study and
-
electrical and computer engineering, including physics, mathematics, signal processing, and machine learning demonstrated by a relevant Ph.D. degree and a scholarly record. For more information on the SPIRAL
-
computing, machine learning/AI, eco-scale application engineering, cloud computing and infrastructure platform design, software driven networking, software engineering/model driven design and architecture techniques
-
Analytics, Data Mining, Machine Learning, Optimization, Systems Simulation, Cloud Analytics, and Computational Tools for Analytics. Proficiency in Python, R, and SQL is an added advantage. While not a
-
technology-enabled financial liberalization (e.g., crowdfunding, non-traditional payment systems, P2P lending, robo- advising), digital assets and currencies, and applications of AI/machine learning in
-
strong mix of experimental and analytical skills, and the ability to communicate complex technical ideas. Qualifications: • A PhD in Electrical Engineering, Computer Engineering, Computer
-
About the Opportunity The Lecturer will teach introductory courses in architectural drawing, sketching, studio design, computer modeling, architectural history, technology, or project case studies