Doctoral Student

Doctoral Student in AI Techniques to Improve Numerical Analysis of Ship Energy Performance We are seeking a highly motivated doctoral student to develop ship physics-integrated machine learning models for real-time prediction and optimization of wind-assisted ship propulsion systems. The project integrates physical ship performance models with operational data and offers a unique opportunity to contribute to sustainable shipping by improving the efficiency and automation of wind-assisted propulsion (WAP) technologies. You will work at the intersection of marine engineering, artificial intelligence, control theory, and human factors, in collaboration with researchers within the Division of Marine Technology at Chalmers University of Technology. The position combines cutting-edge research with the potential to influence future ship designs and operations. If you are passionate about applying advanced technologies in real-world maritime environments, we encourage you to apply. About us The Department of Mechanics and Maritime Sciences (M2) conducts both fundamental and applied research in various modes of transport to achieve sustainable technological solutions. M2 hosts one of Sweden's most extensive simulator centers for navigation and propulsion, as well as world-class laboratories in combustion engineering and wind tunnels. The Division of Marine Technology conducts research and education related to ship operational performance models, including topics such as structural integrity, fatigue and fracture, hull design, risk and reliability analysis, ship resistance and motions, and propulsion systems. About the Research Project This project aims to improve ship energy performance through the integration of AI, big data analysis, and numerical ship analysis. The goal is to develop a digital twin—a virtual replica of a ship's physical systems—that combines real-world sensor data with advanced numerical models of hull, engine, and propeller dynamics. By combining physics-based simulations with data-driven methods, the digital twin will enhance understanding of ship behavior under varying conditions, identify inefficiencies, and support energy-saving strategies. The project contributes to reduced fuel consumption, lower emissions, and improved insight into ship performance in real-world ocean environments. It will be conducted in collaboration with multiple doctoral and postdoctoral researchers in our group, aiming to advance sustainable ship operations. Who We Are Looking For The successful candidate has a Master's degree (masterexamen) of 120 credits or a Master's degree (magisterexamen) of 60 credits* in naval architecture, maritime transport, applied mechanics, or related areas, with a strong background in mathematics, programming, and data processing. You should have relevant knowledge in ship resistance, propulsion, or energy systems, be proactive, and take responsibility for your work. Collaboration is key, as the project involves interaction with adjacent disciplines and industry. You should also be able to communicate and disseminate research results effectively. Required Qualifications: • Excellent academic results • Strong mathematical and statistical analysis skills • Proficiency in programming • Solid theoretical background • Ability to research and work independently • Experience in presenting research results • Fluency in written and spoken English • Dedication and a strong desire to learn Merits: • Programming skills in Python and machine learning • Knowledge of data processing • Familiarity with numerical analysis of ship performance and energy modeling • Experience in writing scientific reports or publications *For candidates with an education completed outside Sweden, a 4-year Bachelor's degree is accepted. What You Will Do Your main responsibility as a doctoral student is to pursue your own research studies, develop scientific concepts, and communicate results. The position is a full-time temporary employment for a maximum of 4.5 years, including up to 15% teaching or other departmental duties. You will be employed by Chalmers and receive a salary according to current agreements. Key Tasks Include: • Developing a digital twin of ship energy systems using AI, big data, and numerical modelling • Integrating real-world sensor data (e.g. wave, speed) with physics-based models of hull, engine, and propeller dynamics • Conducting simulations to study ship performance under varying conditions • Analyzing energy efficiency and identifying operational inefficiencies • Advancing your expertise in numerical modelling and digital twin technologies Contract Terms: • The Doctoral student positions are fully funded from start. • The position is a fixed-term appointment of four years, with the possibility to teach up to 20%, which extends the position up to five years. • A starting salary of 34,550 SEK per month (valid from May 25, 2025). • Doctoral studies require physical presence throughout the entire study period. A valid residence permit must be presented by the study start date; otherwise the admission may be withdrawn.