Start date: from 01.01.2023
The Institute of Earth Surface Dynamics (IDYST) and the Institute of Earth Sciences (ISTE) are hiring a computational geoscientist to develop, maintain, and improve their research codes.
From geodynamics to climate change science via glaciology, our institutes cover a wide range of Earth system applications, most of which rely on numerically solving large systems of differential equations, statistical methods, or both.
This position comes in support to the computational aspects of these projects, including code optimization, the implementation of best practices, and the efficient use of our supercomputing facilities. This is a research position where we expect an intellectual contribution to our projects aimed at solving the geoscientific, environmental, and climatic challenges of our time.
PhD degree in computer science, applied mathematics, or other disciplines involving computational research, such as computational geosciences, or equivalent experience.
Proven record of expertise in programming high-performance algorithms for scientific computing (including parallel computing, machine learning, and numerical methods for physics-based differential equations systems). Familiarity with pertinent computational problems in the Earth, environmental, or engineering sciences, or a strong interest to engage with such topics.
Experience in multiple programming languages (e.g. Python, R, Fortran, C, C++, CUDA, Julia, Matlab) and computing platforms (CPU, GPU, FPGA).
Ability to collaborate with multiple groups and to create bridges across topics and disciplines. Ability to manage complex tasks autonomously.
Excellent skills in written and spoken English is mandatory.
Description of Responsibilities:
Support for optimizing codes (including parallelization), specific for Earth/environmental applications, and for specific hardware (e.g. GPU, FPGA). Optimizing code performances contributes to UNIL's sustainability goals.
Implementation of high-performance and parallel computing related to the numerical solution of systems of PDEs (typically in collaboration with researchers).
Support for the design of models based on machine learning for geoscientific applications (prediction algorithms, numerical schemes, etc.).
Support for best practices in the programming, implementation, distribution, and documentation of code Publication of scientific research in collaboration with other researchers of the Faculty of Geosciences and Environment.
Collaboration with and initiation of scientific research projects.
The application documents must be uploaded as a single PDF file. Any questions can be directed to Prof. Stefan Schmalholz (firstname.lastname@example.org) or Prof. Gregoire Mariethoz (email@example.com).
Application Deadline: October 1st, 2022
More details and applications at this link: https://bit.ly/3B69Jhf
(also accessible through the University of Lausanne jobs portal https://www.unil.ch/carrieres/en/home/menuinst/emplois.html)