Materials Machine Learning Bootcamp 2020

Date: TBD DUE TO COVID-19

Join us for a fully funded eight-week bootcamp on developing and applying cutting-edge machine-learning tools to pressing problems in materials science and quantum simulation

Find Out More

MATERIAL MACHINE LEARNING BOOTCAMP

By developing new, complex representations of data, machine learning has led to powerful modelling approaches in many scientific disciplines. The introduction of these methods to materials science is still recent, and many published applications do not take full advantage of the strengths of machine learning techniques and therefore do not replicate the successes they have had in other fields. The opportunity, however, is enormous: being able to more accurately and more quickly predict the properties of materials would allow promising new catalysts, solar cells, or batteries to be designed computationally, reducing the time and expense of trial and error experimentation in the lab. To take advantage of this opportunity, this targeted Bootcamp will bring together early career researchers to develop new machine learning techniques and apply them to important problems in materials science and quantum simulation.

ABOUT


We will fund up to three participants in each of the three themes, listed below, that sit at the intersection of materials simulation and machine learning. The Bootcamp will strengthen interdisciplinary collaboration via hands on projects that will define the benefits and limitations of machine learning, introduce exciting open problems to the broader community, and stimulate new approaches to solving challenging open problems.


The Bootcamp will take place at the University of Sydney, with its uniquely relevant world-class research initiatives and institutes. The Bootcamp is organised by the Computational Materials Design Grand Challenge project led by A/P Ivan Kassal and Dr Lamiae Azizi, of the Sydney Nano Institute, but will benefit from the great and diverse scientific environment offered by researchers in the Faculty of Science and Engineering, Centre for Translational Data Science (CTDS) and the newly established Data Analytics for Resources and Environment (DARE) and the Sydney Mathematical Research Institute (SMRI). In addition, social activities are planned to help you make friends and take advantage of your stay in Australia and its beautiful environment.



Participants will spend 8 weeks as part of diverse, collaborative research teams, from a date to be decided. While we prefer participants to take part in the entire Bootcamp, we can accommodate some flexibility in start and end dates.


Please direct any inquiries to Dr Lamiae Azizi and Prof Ivan Kassal


Avatar
Avatar
Avatar
Avatar
Avatar

APPLY


We are looking for early career researchers, whether computer scientists, mathematicians, or physical scientists who are experts in machine learning and are interested in developing and applying machine learning techniques to one of the three projects above. We particularly encourage applications from final year PhD students and recent PhD graduates, from anywhere in the world.

We celebrate diversity and are committed to creating an inclusive environment for all our teammates. We especially encourage applications from women, Aboriginal people and Torres Strait Islanders, as well as members of ethnic or cultural minorities or other groups underrepresented in computational and physical sciences.


Participants will not enter into an employment relationship with the University of Sydney, but will have their expenses either covered upfront or reimbursed. Expenses eligible for reimbursement include airfare, visa costs, accommodation and childcare.


Application deadline: Due to COVID-19 the application deadline has been extended indefinitely.