PhD on time-predictable high-performance computing
PhD on time-predictable high-performance computing
Job description
There is a widespread adoption of AI in most application domains, including in safety- and mission-critical systems. This raises new challenges as these systems must undergo certification processes to prove that they will not harm users, by-standers, the environment, other systems or lead to undesirable, unforeseen or dangerous situations. Such safety- and mission-critical systems must therefore meet a combination of safety, domain-specific, and high-performance requirements to execute complex and data-hungry AI-applications in a provably safe manner. This notably include requirements that the system's performance must be predictable and analyzable so as to provide worst-case guarantees that can be used as evidence during their certification.
A major roadblock to achieving time-predictable high-performance computing originates from the complexity of the modern execution platforms designed to meet the computational needs of AI-applications. On such platforms, the need to reduce power consumption while maximizing peak performance results in a high-degree of resource sharing (caches, DRAM, bus, I/Os) causing unpredictable interference, thus preventing guaranteeing that the AI-application's timing requirements will be met once deployed. This is an unprecedented challenge from a safety and real-time perspective.
We look for a PhD candidate who will work on developing a predictable execution platform for AI-oriented computing to achieve higher control over the system's predictability, enable its analyzability —hence providing required properties towards its certifiability—, with no performance degradation.
The project will work towards:
The candidate will integrate with the Interconnected Resource-aware Intelligent Systems cluster at TU/e and the Chair of Cyber-Physical Systems in Production Engineering at TUM.
A major roadblock to achieving time-predictable high-performance computing originates from the complexity of the modern execution platforms designed to meet the computational needs of AI-applications. On such platforms, the need to reduce power consumption while maximizing peak performance results in a high-degree of resource sharing (caches, DRAM, bus, I/Os) causing unpredictable interference, thus preventing guaranteeing that the AI-application's timing requirements will be met once deployed. This is an unprecedented challenge from a safety and real-time perspective.
We look for a PhD candidate who will work on developing a predictable execution platform for AI-oriented computing to achieve higher control over the system's predictability, enable its analyzability —hence providing required properties towards its certifiability—, with no performance degradation.
The project will work towards:
- Developing an execution layer (acting as a middleware) to exploit the capabilities of modern computing platforms to enforce predictable behavior and to efficiently utilize the available computing power through dynamically orchestrating access to shared resources.
- Developing modeling and timing analysis tools to produce evidences usable as safety arguments during certification.
The candidate will integrate with the Interconnected Resource-aware Intelligent Systems cluster at TU/e and the Chair of Cyber-Physical Systems in Production Engineering at TUM.
Specifications
- max. 38 hours per week
- Eindhoven View on Google Maps
:fill(white)/logos/tue-en-wide_acOLN2b.png)
Eindhoven University of Technology (TU/e)
Requirements
- You have a master's degree (or an equivalent university degree) in computer science or electrical engineering.
- You have a strong background in at least two of the following areas: real-time systems theory and/or development, operating systems, (co-)processor design/emulation, high-performance computing and networking.
- We are looking for a talented, motivated and enthusiastic researcher who has analytical skills, initiative and creativity.
- You are a naturally curious person who is eager to learn more and has a strong interest in research.
- You have a team spirit and the ability to work in an internationally oriented environment.
- You are fluent in spoken and written English (equivalent to at least C1 level).
Conditions of employment
A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station of Eindhoven. You will spend extended periods of time (for a total of at least 1/3 of your PhD) at TU Munich in Germany.
In addition, we offer you:
In addition, we offer you:
- Full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks related to your research topic.
- Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. €2,770 max. €3,539).
- A year-end bonus of 8.3% and annual vacation pay of 8%.
- High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
- An excellent technical infrastructure and sports facilities.
- An allowance for commuting, working from home and internet costs.
- A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates meeting the correct requirements.
Additional information
About us
Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow.
The Technical University of Munich (TUM) combines top-class facilities for cutting-edge research with unique learning opportunities for students. The university thinks and acts with an entrepreneurial spirit. Its aim: to create lasting value for society. All this combines to make it one of Europe's leading universities. TUM's alumni include 17 Nobel laureates and 18 Leibniz Prize winners. In 2019, TUM secured the title "University of Excellence" for the third time in succession under the German Universities Excellence Initiative, winning every round since the excellence competition's inception in 2006.
Information
Do you recognize yourself in this profile and would you like to know more about the IRIS cluster at TU/e and the Chair of Cyber-Physical Systems in Production Engineering at TUM? Please, visit https://iris.win.tue.nl and https://rtsl.cps.mw.tum.de.
For questions regarding this position, you can send an email to dr. Geoffrey Nelissen (g.r.r.j.p.nelissen[at]tue.nl) with email subject 'PhD on time-predictable high-performance computing'.
Visit our website for more information about the application process or the conditions of employment.
Are you inspired and would like to know more about working at TU/e? Please visit our career page.
Application
We invite you to submit a complete application by using the apply button. The application should include a:
We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.
Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow.
The Technical University of Munich (TUM) combines top-class facilities for cutting-edge research with unique learning opportunities for students. The university thinks and acts with an entrepreneurial spirit. Its aim: to create lasting value for society. All this combines to make it one of Europe's leading universities. TUM's alumni include 17 Nobel laureates and 18 Leibniz Prize winners. In 2019, TUM secured the title "University of Excellence" for the third time in succession under the German Universities Excellence Initiative, winning every round since the excellence competition's inception in 2006.
Information
Do you recognize yourself in this profile and would you like to know more about the IRIS cluster at TU/e and the Chair of Cyber-Physical Systems in Production Engineering at TUM? Please, visit https://iris.win.tue.nl and https://rtsl.cps.mw.tum.de.
For questions regarding this position, you can send an email to dr. Geoffrey Nelissen (g.r.r.j.p.nelissen[at]tue.nl) with email subject 'PhD on time-predictable high-performance computing'.
Visit our website for more information about the application process or the conditions of employment.
Are you inspired and would like to know more about working at TU/e? Please visit our career page.
Application
We invite you to submit a complete application by using the apply button. The application should include a:
- Cover letter in which you describe your motivation and qualifications for the position.
- Curriculum vitae, including a list of your publications and the contact information of three references.
- Transcripts of your BSc and MSc grades
- At least one recent support letter
We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.
Specifications
- PhD
- Engineering
- max. 38 hours per week
- University graduate
- V32.6879
Employer
Location
Interesting for you
Apply for this job
Apply for this job
This application process is managed by the employer (Eindhoven University of Technology (TU/e)). Please contact the employer for questions regarding your application.
Thank you for applying
Please contact the employer for questions regarding your application.
Tip: save this job as favorite in your AcademicTransfer account. This gives you an immediate overview and makes it easy to find the job later on. No account yet? Create it now and take advantage of other useful functionalities too!
Application procedure
Application procedure
Make sure to apply no later than 6 Oct 2023 23:59 (Europe/Amsterdam).