Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
strong mix of experimental and analytical skills, and the ability to communicate complex technical ideas. Qualifications: • A PhD in Electrical Engineering, Computer Engineering, Computer
-
the following training will be considered PhD in computer science, machine learning, AI or related computational field, or, Ph.D. in a health-related discipline with experience in experimental science, devices
-
of interest include machine learning, LLMs and SLMs, natural language processing, computer vision, theory, and transparent and explainable AI models. Human Centered AI: areas of interest include sensing and
-
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
-
related to cognitive and distributed RF signal processing and machine learning, unmanned and autonomous system technologies, advanced manufacturing, as well as quantum materials and sensing. KRI has and is
-
and distributed RF signal processing and machine learning, unmanned and autonomous system technologies, advanced manufacturing, as well as quantum materials and sensing. KRI has and is expanding
-
teaching and other learning objectives: (4) Experiential learning and stakeholder support; and (5) Design and implementation of recruitment strategies for the academic programs, working with Northeastern
-
Lab researches on a variety of computer systems topics including HPC resilience, data center power management, large-scale job scheduling and performance tuning, parallel storage systems and scientific
-
About the Opportunity SUMMARY The lab of Professor Albert-László Barabási is looking for Postdoctoral Research Associates in the area of network science, nutrition, biological networks, machine