Postdoc Human-Centred Thermal Comfort and Machine Learning for Electric Vehicles

.jobdescription td { padding: 0 5px; } .jobdescription * { border: none !important; border-width: 0 !important; font-size: 12px !important; font-family: Arial, Helvetica, sans-serif !important; color: black !important; } .jobdescription h1 b, .jobdescription h2 b, .jobdescription h3 b, .jobdescription h4 b, .jobdescription h1, .jobdescription h2, .jobdescription h3, .jobdescription h4 { font-size: 14px !important; font-weight: bold; margin-bottom: 0.5em !important; } #search-wrapper{display:none;} /* TUDelft Sidebar style */ .jobColumnTwo .joblayouttoken { background: #e3e3e3; color: #011b3c; padding: 0 20px 5px !important; } .jobColumnTwo .joblayouttoken .joblayouttoken-label { color: #039fd8; font-weight: bold; } .jobColumnTwo .joblayouttoken.marginTopLarge { padding: 20px 20px 5px 20px !important; } .jobColumnTwo .joblayouttoken.marginBottomLarge { padding: 0 20px 20px 20px !important; } /* TU Delft full-width header image */ .topleft.verticallyscaled.backgroundimage.large-image-component { height: 0 !important; } div[role='img'] .topleft.scaled.large-image-component{ height: 0 !important; position: absolute; padding-top: 20% !important; background-position: center !important; top: 50px; } div.job{ position: relative; padding-top: 26% !important; } /* Fix voor niet werkende knop */ div.jobTitle{ z-index: 2; position: relative; margin-top: 5px; } Postdoc Human-Centred Thermal Comfort and Machine Learning for Electric Vehicles Job description The Intelligent Vehicles (IV) group* at TU Delft aims to increase the safety, comfort and sustainability of transportation by means of automated driving. The group conducts problem-driven research within the interdisciplinary spectrum of machine perception, dynamics and control, and human factors. * Website: intelligent-vehicles.org, YouTube: youtube.com/c/IntelligentVehiclesatTUDelft We are seeking a highly motivated researcher to contribute to the development of next-generation thermal comfort technologies for Battery Electric Vehicles. The successful candidate will develop advanced thermal comfort metrics by combining physiological measurements, subjective user feedback, and environmental data. The research will involve machine learning, human-centred experimentation, real-time comfort prediction, and the integration of intelligent climate control systems into vehicle platforms. The position includes the design and execution of simulator-based studies, development of predictive comfort models, and validation of thermal comfort solutions using diverse participant groups. This position is part of an ongoing EU project AETHER (Advanced Thermal Comfort and Energy Management for Personalized, Efficient and Weather-Aware Electric Vehicle Operation) involving several partners from the automotive industry and from research institutions across Europe. The candidate will: Develop advanced thermal comfort metrics using multimodal physiological, environmental, and subjective assessment. Design and implement machine learning algorithms for real-time prediction of occupant thermal comfort. Analyse physiological signals including skin temperature, skin conductance, heart rate, and wearable sensor data. Develop and validate comfort prediction models targeting high prediction accuracy using a dynamic driving simulator and real-world operating conditions. Integrate thermal comfort models into vehicle climate control systems for adaptive heating, cooling, and ventilation strategies. Design, conduct, and analyse human-subject experiments involving diverse participant groups. Collaborate with academic and industrial partners on system integration, validation, and dissemination activities. Publish research findings in leading scientific journals and present results at international conferences. Within AETHER the candidate will collaborate with industrial and academic partners focusing on thermal comfort modelling and assessment. Within TU Delft, the candidate