About Jonathan Nuttall

Dr Jonathan Nuttall has a PhD in Geotechnical Engineering, Numerical Modelling, Data Science, HPC and Software Development. During his PhD he developed a High-Performance Computing (HPC) framework for the Random Finite Element Method (RFEM), in his thesis entitled “Parallel Implementation and Application of the Random Finite Element Method”.

At Deltares he is the lead of the Data Science pillar within the Enabling Technologies initiative, providing research, guidance and education in the fields of Data Science and Machine Learning. Introducing new and disruptive techniques into the Deltares work flows and research. His central research focuses on the area of Physics based Machine Learning techniques and the development of Machine Learned tools for stakeholder decision making.

Jonathan was also a former member of the Deltares Young Science Council which advised the Board of Directors on innovation in science and technology. He also has active collaborations with TUDelft, Rijkswaterstaat, and the University of Leeds in the fields of Machine Learning and Artificial Intelligence, while he is an active member of the Anura3D MPM community (http://www.anura3d.com/), developing the Material Point Method for Geotechnical Applications and is lead developer for the Geolib+ project, developing innovative open source tools for use with the Geolib library, providing pre and post processing tooling for use with Deltares D-Series products, and other Geotechnical tools.