By Erin Warner
The University of Toronto’s Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship, a program of Schmidt Futures, is pleased to announce its first cohort of 10 fellows. U of T is one of nine universities around the world, and the only one in Canada, to be selected for this $148-million program to support the use of artificial intelligence (AI) in research.
From climate change to infectious disease, AI can help us solve the biggest challenges of our time by accelerating the pace of scientific research and development. U of T’s Eric and Wendy Schmidt AI in Science Postdocs program boosts the work of early-career scholars in engineering, mathematics and natural science by giving them vital tools in AI.
The fellowship includes networking and research collaborations between participating universities; a robust series of workshops, conferences and lectures; and training in how to apply AI techniques. To maximize accessibility and impact, fellows do not need prior experience with AI but will leave the program as AI-fluent scientists, ready to expand new research methodologies across a range of fields through their future work.
‘It is an exciting time to be part of the AI revolution that is fundamentally changing the way we do science’
“My warmest congratulations to the first cohort of Schmidt AI in Science post-doctoral fellows. It is an exciting time to be part of the AI revolution that is fundamentally changing the way we do science,” says Timothy Chan, U of T’s associate vice-president and vice-provost, strategic initiatives. “I wish you great success in your training and research at U of T.”
“U of T’s Schmidt AI in Science Postdoc program will equip fellows with AI tools and training that will transform and accelerate their research, ultimately helping catalyze novel solutions to many of the daunting challenges we face,” says Alán Aspuru-Guzik, director of U of T’s Acceleration Consortium and co-lead of the Schmidt AI in Science Postdoc program.
“Thank you to Schmidt Futures for developing a program that is interdisciplinary and accessible––an opportunity that will allow young scientists to take risks with new techniques to drive real innovation,” says Lisa Strug, director of U of T’s Data Sciences Institute and co-lead of the Schmidt AI in Science Postdoc program.
To review the past call for Schmidt AI in Science Postdocs and stay in the loop about future calls for proposals, please visit schmidtfellows.utoronto.ca.
U of T’s Eric and Wendy Schmidt AI in Science Postdocs
Meet the inaugural cohort of U of T’s Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship and learn what grand challenges they aim to solve using AI:
Daniel Gilman: the mysterious properties of dark matter
Research goal: To identify and understand the properties of dark matter, one of the most confounding mysteries in cosmology.
Soumita Ghosh: early detection of non-alcoholic fatty liver disease
Research goal: To discover consistent biomarkers, leading to non-invasive tests for large-scale screening, early detection and individually customized interventions for Non-Alcoholic Fatty Liver Disease, the most common chronic liver disease in Canada.
Md Abdul Halim: mitigating methane emissions for smart cities
Research goal: To quantify and monitor point-source methane emissions, which traps 25 times more heat than carbon dioxide, from urban landscapes and develop effective mitigation strategies for climate smart cities.
Jessica Leivesley: revolutionizing fish population management
Research goal: To revolutionize the monitoring and management of commercially important fish populations through non-invasive and non-lethal methods.
Tianyuan Lu: genetic disease prevention for underrepresented ancestries
Research goal: To improve the prevention of complex diseases by better understanding an individual’s genetic predispositions, especially for individuals of non-European ancestries who are vastly underrepresented in the data.
Soukayna Mouatadid: accurate forecasting for weather event management
Research goal: To improve the accuracy of sub-seasonal forecasting to better respond to weather events, including decisions related to water allocation, wildfire management, and drought and flood mitigation.
Gerard O’Leary: devices to treat neurological disorders
Research goal: To better understand mechanisms of neurological disorders and to accelerate the deployment of neuroelectronic medical devices to treat them, devices which have already shown great promise in reducing symptoms of brain-related disorders, such as tremors and seizures.
Felix Strieth-Kalthoff: sustainable molecules for medicine, agriculture and materials
Research goal: To make molecules sustainably and efficiently for different (chemical) industries, ranging from modern medicine and drug development to agrochemistry and performance materials.
Daoye Zhu: sustainable natural-urban ecosystems
Research goal: To improve our understanding of a wide range of biophysical, ecosystem and socio-economic changes in order to create sustainable natural-urban ecosystems.
Fatema Tuz Zohora: anti-cancer drug resistance
Research goal: To improve anti-cancer drug resistance in humans, which is responsible for up to 90 per cent of cancer related deaths, despite vast improvements to date.