PhD position in computer science, AI in advanced thermal management

Mälardalen University (MDU) is the youngest university in Sweden. In line with our vision, to be a progressive and collaborative University where we shape a sustainable future together, we wish to make a difference.

Do you want to be involved and contribute to our development?

Together, we can create a sustainable future through knowledge and innovation. We believe that knowledge and new perspectives are best attained and reached together in collaboration with others – our colleagues, students, the private and public sectors, both nationally and internationally

At the School of Innovation, Design and Engineering our students are studying to be for example innovators, entrepreneurs, illustrators, communications officers, network technicians and engineers. Here we have the research specialisations of Embedded Systems, and Innovation and Product Realisation. Our work takes place in cooperation with and in strategic agreements with companies, organisations and public authorities in the region.

Employment: Temporary employment
Scope: Full time
Closing date for application: 2024-01-08
Campus location: Västeras
School: School of Innovation, Design and Engineering, (IDT)

We offer a PhD student position in computer science.

Research will be conducted within project Enhanced Reliability, Monitoring and Diagnostics of Complex Cooling Systems through Advanced Thermal Management (HeatTrack) of the competence center RESILIENT. This project will focus on studying and developing optimization, monitoring and diagnostics methods and tools dedicated for complex industrial cooling systems. A healthy cooling system will strengthen the resilience of a complex energy system. However, a defective cooling system can dramatically reduce the overall system resilience.

The heat track project will also serve as a platform to evaluate using AI/ML as physics-informed neural networks (PINNs) to strengthen/complement the Computational Fluid Dynamic (CFD) simulations. The academic and industrial partners will support the project with available data and deep process knowledge.

Only those who are or have been admitted to third-cycle courses and study programmes at a higher education may be appointed to doctoral studentships. For futher information see Chapter 5 of the Higher Education Ordinance (SFS 1993:100).

 The applicant should have a B.SC/M.Sc. or four years of study (240 higher education credits) with at least one year (60 credits) of a second-cycle degree in Computer Science or Computer Engineering. Proficiency in English, both written and oral, is required.

The PhD should have an interest in both applied and theoretical research work and should have knowledge in:

• AI, Deep Learning, and probability theory
• Computer vision, and image processing
• Programming experience is required such as knowledge of Python, and related libraries e.g., Tensorflow or PyTorch and Pandas etc.

Decisive importance is attached to personal suitability. We value the qualities that an even distribution of age and gender, as well as ethnic and cultural diversity, can contribute to the organization.

The following qualifications are considered to be a merit:

• Knowledge of physics-informed neural networks (PINNs)
• Outstanding academic record

Application is made online. Make your application by clicking the "Apply" button below.

The applicant is responsible for ensuring that the application is complete in accordance with the advertisement and will reach the University no later than closing date for application.

We look forward to receiving your application.

We decline all contact with recruiters and salespersons of advertisements. We have made our strategic choices for this recruitment.

Union representatives:

Michaël Le Duc (SACO), tel: +46 (0) 21-10 14 02
Susanne Meijer (OFR), Tel: +46 (0) 21-10 14 89

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