12 phd-position-in-data-modeling-"Prof"-"Prof" PhD positions at Chalmers University of Technology
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We are looking for a PhD candidate fascinated in modelling erosion processes in sensitive clay slopes. The highly sensitive clays, called quick clays, can change from solid to liquid with small
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Experience with performing laboratory experiments Ability to work with large data sets (> 500 GB) Numerical modelling Main responsibilities Independent research and research training (80% of time) Support for
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qualifications Marine biogeochemical processes Hydrodynamic processes related to ships, turbulence, or mixing Oceanographic modelling Data analysis and programming (e.g., MATLAB, Python, or R) Interdisciplinary
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We are looking for a PhD student to join our cutting-edge research in nanoelectronics for terahertz applications. You will explore advanced semiconductor devices and circuits, shaping the future
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cells. Reference number: 20250273 Application deadline: August 10, 2025 Project overview This 5-year PhD project aims to develop a flexible and general model that enables comparison between different
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background and your motivation to pursue a PhD • Motivate your interest in the research topic of this position and in pursueing your PhD at Chalmers • Describe your current MSc project and/or future research
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start date; otherwise, admission may be withdrawn. What we offer: The PhD positions are fully funded from start As a PhD student at Chalmers, you are an employee and enjoy all employee benefits. Read more
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140 PhD students at CSE. Your main supervisor will be Prof. Nir Piterman, with support from a co-supervisor and an examiner. Supervision is structured to guide your academic development, with regular
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This PhD position at Chalmers University of Technology offers an exciting opportunity to work in an interdisciplinary environment and receive training and support in materials design and synthesis
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This PhD position offers a unique opportunity to advance safe and transparent control for autonomous, over-actuated electric vehicles. You will work at the intersection of model predictive control