Doctoral student in acoustic source characterisation KTH Royal Institute of Technology in Sweden

Doctoral student in acoustic source characterisation at KTH Royal Institute of Technology

This PhD position is part of a project in the FFI Zero Emissions programme focused on acoustic source characterisation of electric vehicle components. The project is carried out in close collaboration between KTH and Volvo Technology AB and addresses the changing noise landscape of electrified vehicles, where combustion noise is replaced by dominant sources such as electric motors, cooling fans, and power electronics.

The research aims to develop robust methods for identifying and characterising these acoustic sources. The work includes equivalent source modelling, inverse acoustics for partially coherent source fields, optimal microphone-array placement, and physics-informed as well as data-driven machine learning. The methods are linked to virtual pass-by simulation, supporting more cost- and energy-efficient vehicle development.

The doctoral student will be based in the Sound and Vibration research environment at the Marcus Wallenberg Laboratory for Sound and Vibration Research, Department of Engineering Mechanics, KTH, and will also be associated with the Centre for ECO2 Vehicle Design. This is a research-intensive PhD within a strong academic–industry collaboration setting.

Eligibility requires basic qualification for postgraduate education under the Swedish Higher Education Ordinance, typically a second-cycle degree such as a master’s degree, or equivalent academic preparation. The applicant must have knowledge corresponding to at least 60 second-cycle credits in Engineering Mechanics, Applied Physics, Electrical Engineering, Vehicle Engineering, or another subject relevant to acoustics, sound and vibration, or signal processing. English proficiency equivalent to English B/6 is mandatory.

Meritorious backgrounds include acoustics, vibration, structural dynamics, signal processing, inverse methods, microphone arrays, machine learning, physics-informed machine learning, and scientific programming with tools such as Python, MATLAB, TensorFlow/PyTorch, COMSOL, or Actran. KTH emphasizes goal orientation, perseverance, independence, collaboration, professionalism, and the ability to handle complex problems.

The employment is a temporary full-time doctoral position with salary according to KTH’s doctoral student salary agreement. The position is advertised as one vacancy in Stockholm, Sweden. Application materials must be submitted through KTH’s recruitment system and include diplomas and transcripts, evidence of language qualifications, a CV, a motivation letter, and representative publications or technical reports. The deadline is 2026-09-24 at 23:59 (CET/CEST).