Monday 17.08.2020 - Friday 21.08.2020
TU Dresden (Germany)
Innovative materials are one of the key technologies for keeping products and industrial processes economically competitive and ecologically sustainable. Modern materials science requires a multi-discipline approach embracing chemistry, physics, engineering, as well as data science. This summer school will provide an overview of current developments in data-driven materials science involving Machine Learning and modern numerical techniques and will offer a platform for discussions about future perspectives.
Materials innovations enable new technological capabilities and drive major societal advancements but typically require long and costly development cycles. Materials Genome Engineering aims at realizing the transition to a new paradigm in materials development from a traditional "trial and error" mode to a "rationally designed experiments" mode. In this highly promising approach, thorough and reliable theoretical prediction and high-throughput screening are followed by experimental verification and technological implementation. Complementary efforts and the seamless integration of theory, computation and experiment, will result in a remarkable acceleration of the pace of new materials discovery, design and deployment. To fully take advantage of its potential, this novel scheme has to rely on cross-innovation and convergence of various scientific fields such as materials science, computer science, physics, chemistry as well as information and data science.
The summer school targets Master students, Ph.D. students and (early-stage) Postdocs interested in or working on topics related to computational and experimental high-throughput approaches, machine learning and data-driven materials science. For excellent students, up to 10 all-inclusive grants (travel support, accommodation, participation) will be available. More information are provided below.
Arrival & Registration:
Sunday, 16th August
Saturday, 22nd August
Applications will be accepted from March onwards until the end of April. The summer school targets Master students, PhD students and early-stage post-docs working on or interested in computational and experimental high-throughput approaches, topics related to machine learning and data driven materials science. To apply for the school the following documents are needed (and have to be uploaded as PDF)
The summer school will take place
in room 229 of Görges building (Helmholtzstraße 9)
which is located on the main campus of TU Dresden