2017 Summer School on Machine Learning in the Molecular Sciences

Summer School Introduction

The NYU-ECNU Center for Computational Chemistry at NYU Shanghai announces a summer school dedicated to machine learning and its applications in the molecular sciences to be held this June at the NYU Shanghai Pudong Campus. Using a combination of technical lectures and hands-on exercises, the school aims to instruct attendees in both the fundamentals of modern machine learning techniques and to demonstrate how these approaches can be applied to solve complex computational problems in chemistry, biology, and materials science.  

Fundamental topics to be covered include basic machine learning models such as kernel methods and neural networks optimization schemes, parameter learning and delta learning paradigms, clustering, and decision trees.  Application areas will feature machine learning models for representing and predicting properties of individual molecules and condensed phases, learning algorithms for bypassing explicit quantum chemical and statistical mechanical calculations, and techniques applicable to biomolecular structure prediction, bioinformatics, protein-ligand binding, materials and molecular design and various others.

Date

June 12 - June 16, 2017

Venue

NYU Shanghai | 1555 Century Avenue, Pudong, Shanghai, China
上海纽约大学 | 中国上海市浦东新区世纪大道1555号

Summer School Website

www.computational-chemistry-workshop.org/homepage-2017