RESEARCH AREAS
We offer unique entrances to future-oriented research areas that merge data-driven technology with science, catalyzing advancements in fields such as chemistry, biology, and earth sciences. These areas are both designed to equip learners with a profound understanding of particular scientific fields as well as hands-on experience, enabling significant contributions to each area.
Digitalization of Chemistry
This course explores the integration of digital technologies in chemistry, focusing on computational modeling, data analytics, and machine learning. Students will delve into the usage of various digital platforms and software that aid in advancing chemical research, simulations, and the creation of digital chemical databases. Through hands-on experiences, students will acquire comprehensive insights into the role and application of digitalization in contemporary chemistry.
Computational Biology
Computational Biology combines quantitative analytical techniques and biological studies, allowing students to model and solve complex biological and biomedical problems. The course covers genomic sequencing, structural biology, evolutionary biology, and mathematical modeling. By the end of this course, learners will have mastered the use of advanced computational tools and the methods to analyze biological data and predict biological function and structure.
Accelerated Discovery
This course illuminates the methodologies and technologies enabling the accelerated discovery of new drugs and materials, with a focus on machine learning, high-throughput screening, and computational modeling. Students will learn about the synergy between computational and experimental methods to optimize material discovery in various domains such as energy storage and healthcare. By the end, students will be adept in utilizing automation in material science, allowing them to make their own contributions to their field.
Digital Earth Sciences
Digital Earth Sciences course provides insights into the transformative role of digital technologies like geographic information system (GIS), remote sensing, and machine learning in studying Earth and its processes. This course integrates both theory and practical applications to offer a comprehensive understanding of digital modeling and simulation techniques used to study Earth’s dynamic systems. Students will acquire substantial knowledge and experience in employing digital tools to research Earth and its environment, addressing complex geological and environmental questions such as predicting wildfires.