Computational statistics harnesses the power of sophisticated numerical algorithms and high‐performance computing to solve complex inferential problems that are intractable by traditional analytical ...

This course is designed for engineering graduate students who are interested in furthering their knowledge in advanced and emerging methods of engineering design, with the focus on computational ...

Data really powers everything that we do. Research activities in the data science area are concerned with the development of machine learning and computational statistical methods, their theoretical ...

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...

The Computational and Statistical Genomics group is based at FIMM–EMBL and works at the interface of computational genomics, population genetics, and large-scale human datasets. Our research focuses ...

A computational method for finding transition states in chemical reactions, greatly reducing computational costs with high reliability, has been devised. Compared to the most widely used existing ...

You'll learn to rigorously and creatively apply computational methods to social science research problems. You'll develop advanced skills in computational methods, research design, social scientific ...

Numerical programming and computer simulations are ubiquitous through all subjects in physics. Thus, computational physics has grown to be an appealing field for those who wish to acquire advanced and ...

A paper published in Biology Methods and Protocols, indicates that a new computational method may help researchers identify ...