Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
on Wednesdays and Fridays 11:35-12:55 and labs Mondays 15:35-17:25. This course includes an Introduction to problem-solving methods and algorithm development. Emphasis is on designing, coding, debugging, and
-
have earned a PhD degree by the time of appointment, or shortly thereafter. Alternatively, applicants must have a Master’s degree with at least five (5) years of teaching experience. Relevant fields
-
signal processing algorithms on FPGA, optimized to significantly improve the resolution of real-time energy measurements made by the ATLAS Liquid Argon Calorimeter system. Use novel high-level synthesis
-
), debuggers, code verifiers and unit test frameworks and gain experience in graphical user interface design and algorithm development. Posting end date: July 11, 2025 Number of positions (est): One (1) position
-
collaboration with industry partners. This work will apply optimal control theory, including machine-learning algorithms and Bayesian estimation, to coherent control of nitrogen-vacancy centers in diamond
-
Sessional Lecturer - AMS402H1F: Interfacing Cultures: AI, Platforms, and Algorithmic Politics Across
Study of the United States is seeking to hire one Sessional Lecturer for the following course: Course number and title: AMS402H1F: Interfacing Cultures: AI, Platforms, and Algorithmic Politics Across
-
AI algorithms applied to medical images To lead effort on enabling translational and physician-in-the-loop AI solutions for medical imaging QUALIFICATIONS Successful applicants will have: a PhD in
-
scientists, nuclear medicine physicians) to develop and implement innovative AI algorithms applied to medical images To lead effort on enabling translational and physician-in-the-loop AI solutions for medical
-
Studies (PhD) Teaching in the age of algorithms: Resisting the algorithmic order through co-created sociotechnical experiments View All Stories Further Information Allocations Funding will be allocated
-
, sometimes from multiple jurisdictions, to achieve sample sizes appropriate for training algorithms. This creates challenges with data security and data flows (due to legislative restrictions). Further, data