Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
, or a related field of thermal nanophotonics. Excellent publication records will be preferred. Experience in matlab, MEEP, RCWA and other softwares and algorithms. Excellent publication track records
-
, quantum machine learning, quantum algorithms from well-established universities/institutes. The candidates must be highly motivated in multidisciplinary research. He/she must have proven experience in
-
, roundtables, and focus groups, ensuring logistical needs are met. - Prepare and distribute detailed meeting agendas and related documents, ensuring timely distribution to relevant stakeholders via mailing lists
-
. Work with Learning@NIE editors to produce and distribute the publication on a regular schedule. Assist in the administration and promotion of NIE Teaching and Learning Committee’s Incentivising ICT Use
-
channels. • Manage and organise brand assets, ensuring consistent application in internal and external communications. • Assist in drafting and distributing press releases and media kits. • Monitor
-
, and cable labelling. Maintain proper documentation and reports for auditing and tracking purposes. Assist the teaching modules for distributing and tracking small lab equipment to the students as
-
algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
-
algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
-
to contributions in top-tier international journals and real-world implementations. Responsibilities: Develop and refine algorithms for decision optimization and risk control, utilizing big data and advanced
-
the essentials of linear algebra, calculus, probability, statistics, algorithms, and data structures. The goal is to provide a foundational understanding of machine learning and deep learning methods