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Engineers developed a ping-pong-playing robot that quickly estimates the speed and trajectory of an incoming ball and precisely hits it to a desired location on the table.
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Postdoc/PhD/MASc/MEng Graduate Research Opportunities at
Artificial Intelligence for Aerospace Systems (AIAS) Laboratory
Department of Aerospace Engineering
Toronto Metropolitan University, Toronto, Canada
1) Artificial Intelligence and Machine Learning-Powered Smart Aerospace Systems
The thesis/project will focus on designing novel artificial intelligence and machine learning-based algorithms to develop smart aerospace systems. Several investigations have been conducted at the AIAS laboratory in cooperation with aerospace companies and government agencies (including NASA, Canadian Space Agency, and MHICA) on the fault diagnosis, prognosis and recovery of aerospace systems. The results on aircraft/spacecraft control systems and aircraft engines are very promising for practical applications. The proposed research aims to further enhance the performance of these algorithms using artificial intelligence, machine learning and digital twins based methodologies for real-time fault diagnosis, prognosis and recovery applications.
2) Cutting-Edge Internet-of-Things (IoT) Devices for Smart Aerospace Systems
In recent years, significant advancements have been made in
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Chemists funded by the U.S. National Science Foundation have developed a new process to synthesize a plant-based compound that shows effectiveness against triple-negative breast cancer cells. According to the American Cancer Society, triple-negative breast cancer is one of the most aggressive types of breast cancer and accounts for 10-15% of all breast cancer cases. The process also increases the compound’s potency against these cancer cells and provides a method for it to be mass-produced to enable further testing as a potential treatment.
The new process can also be used broadly to help discover new medicines by synthesizing and testing other complex organic compounds. The findings were achieved by Emory University researchers and published in The Journal of the American Chemical Society.
The compound — called phaeocaulisin A — is extracted from the flowering plant Curcuma phaeocaulis, a relative of ginger and turmeric used for centuries in traditional medicine.
“We not only efficiently replicated a complex natural product, we also improved upon it by turning it into a more potent compound,” says Mingji Dai, professor of chemistry and co-lead of the study.
“It is only the first step in a long process,” says Yong Wan, professor of pharmacology and chemical biology and study co-lead. “But the new analogue of phaeocaulisin A we have reported shows promising efficacy against triple-negative breast cancer cells, which are very aggressive and
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SDU Center for Large Structure Production (LSP), part of the Maersk Mc-Kinney Moller Institute (MMMI) at University of Southern Denmark (SDU), invites applications for one or more fully funded Associated Professor positions in the area of model- and simulation-based planning and control of robotic production systems. The positions will be vacant from August 1, 2025, or as soon as possible thereafter for a. Main work location is Odense/Denmark at SDU and Odense Havn (Odense Port).
Work environment
The candidate(s) will be part of SDU’s newly established SDU Center for Large Structure Production (LSP). LSP’s central ambition is to provide a physical “go-to” lab for companies in the sectors maritime, construction and energy to carry out research, development and testing of novel solutions in the production of large structures, such as buildings, ships and offshore platforms. In this context, the candidate is expected to work closely with our
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