项目介绍

2026年9月17日

About the position

Long term management of large scale computing infrastructures requires detailed knowledge of the performance parameters that affect their application software, as it aids in making future technology choices, predicting performance and scalability, and adapting critical software to new developments.

The candidate will join the System Software Group, and study the performance and scalability characteristics of adapting scientific simulation software to current and future supercomputer hardware. The research work will be informed by collaborations with the scientific computing team that manages the local HPC resources at NTNU, and Uninett Sigma2, which manages both the Norwegian national infrastructure for HPC in Norway, and international connections.

Are you motivated to take a step towards a doctorate and open up exciting career opportunities? As a PhD Candidate with us, you will work to achieve your doctorate, and at the same time gain valuable experience that qualifies you for a further career in higher education and research, in and outside academia.

Your immediate leader will be the head of the computing unit. 

About the project

The primary research goal will be to create quantitative performance models that describe a range of numerical methods, parallel programming models, and hardware platforms when we apply them to the CFD problem of simulating the sloshing motion of a fluid within a moving tank.

The purpose of these experiments will be to identify the hardware/software interactions that dominate the parallel scalability of similar simulations, with a view towards informing future technology choices in the HPC sector.
 

Duties of the position

• Complete the doctoral education until obtaining a doctorate
• Carry out research of good quality within the framework described above
• Academic publications and popular science dissemination
• Participate in international activities such as conferences and/or research stays at foreign educational institutions
• Coordinating and managing the practical exercises in a course on parallel computing.
   

Be prepared for changes to your work duties after employment.

Required selection criteria

• You must meet the requirements for admission according to Section 6-1 of the PhD regulations.
• You must have a relevant Master’s degree in computer science or equivalent. Your degree must include a major independent project (minimum 30 ECTS) equivalent to a master’s thesis.
• You must have a strong and relevant academic background from your previous studies and have an average grade from your Master’s degree study, or equivalent education, which is equal to B or better compared to NTNU’s grading scale. If you do not have letter grades from previous studies, you must have an equally good academic foundation. If you have a weaker academic background, you may be considered if you can document that you are exceptionally suited for a PhD education, for example through relevant work experience and/or peer-reviewed academic works.
• Good oral and written presentation skills in English.
• You must have prior experience with the MPI and OpenMP programming models, and provide an example of a CFD simulation program you have contributed.
   

The appointment is to be made in accordance with NTNUs guidelines for recruitment positions for general criteria for the position.

Preferred selection criteria

• Good oral and written presentation skills in Norwegian, or another scandinavian language
• Experience with the CUDA programming model for general-purpose GPUs
• Experience with the OpenCL programming model
• Experience with the SYCL programming model

Personal characteristics

To complete a doctoral degree (PhD), it is important that you are able to: 

• Work independently
• Work in a structured way, set goals and make plans to achieve them
• Present and discuss your research with other professionals
• Get involved and contribute constructively with feedback
• Work constructively under pressure or in the face of adversity 
• Show curiosity and a strong motivation for the subject
• Analyze data, assess different perspectives and draw well-founded conclusions 
• Be flexible and open to adjusting the plan for the project as needed
   

Emphasis will be placed on personal qualities.