JADS: PhD in Engineering Data & AI Supremacy in the Semiconductor Industry

JADS: PhD in Engineering Data & AI Supremacy in the Semiconductor Industry

The Jheronimus Academy of Data Science (JADS) is the joint Data Science Academy of Tilburg University and Eindhoven University of Technology, the Netherlands. JADS is seeking an enthusiastic colleague for the position of PhD in AIOps and Dynamic, Explainable Orchestration (1.0 fte)

Job description

In a world that is getting smarter (smart cities, smart cars, etc.) there is a growing demand for chips (semi-conductors) that provide products with intelligence and connectivity, in a secure way. Several markets (automotive, consumer electronics) are severely impacted by shortage of chips. NXP is an R&D company that exploits latest technologies (16 nm FF, 7 or even 5 nm) with their innovations and within their industrial pipelines. To give NXP a competitive advantage in the complex market segment represented by semiconductor design, we are aiming for a research end-goal we term Data & AI supremacy, meaning that their AI-driven infrastructure, MLOps pipelines, data-lakes and engineering facilities all work in a measurable synergy with the organisational structure around, that is, also reflecting a measurable organisational performance to the benefit of key strategic objectives defined in NXP’s current and future operational models. This project will seek to elaborate on this ambitious goal by means of the most advanced techniques in the state of the art—e.g., chaos engineering for smarter infrastructures management or organisational culture management to track organisational performance—as well as tight interaction with the state of practice, with a specific eye on the practice around the High-Performance Compute architectures and infrastructure operations that are close to the aforementioned operational models in NXP.

The project is a collaboration of the Jheronimus Academy of Data Science (JADS), ‘s-Hertogenbosch (campus Mariënburg), Tilburg University (TiU), Eindhoven University of Technology (TU/e) and the commercial, industrial and academic partners part of the action, specifically, NXP, one of our closest partners, market leader in semiconductor research and development.

NXP’s technical solution currently heavily draws data from a centralized data-lake that combines and partially cures data from a series of edge-enabled and hybrid cloud data sources. Currently, data pipelines are developed for the purpose of specific ML/AI jobs. Unfortunately, however, this centralistic approaches comes with various challenges. Firstly, the operational capacity of such a centralized data team can become a serious bottleneck for robust and scalable data sharing. Secondly, since the centralized team is logically separated from the (decentral) business domains, it becomes exceedingly difficult to serve high-quality data in line with the consumer’s needs. Lastly, it becomes ever more challenging to (re) develop, deploy and manage high-performance compute data pipelines as their number grows quickly.

As part of a larger initiative and with the explicit need to collaborate with other PhD who will be focusing more on Data-Scientific and analytic aspects, This PhD shall start from a synthesis of both the state of the art and practice and shall look into ways in which supremacy can be defined, theorised, implemented, and what automations can be provided to make its institutionalisation more straightforward.

Profile
The research will be conducted under supervision of Prof. Dr. Willem-Jan van den Heuvel and Dr. Damian A. Tamburri. The students are expected to deliver both long-term results (understanding of machine learning in quality evaluation of software-defined infrastructures) and mid-term results (algorithms, approaches, high-impact/high-relevance papers, and best practices).

The successful candidate is expected to:

  • Perform scientific research in the domain described.
  • Develop software that implements the algorithms described.
  • Present results at (international) conferences.
  • Publish results in scientific journals.
  • Participate in activities of the group, mainly in ‘s-Hertogenbosch but sometimes also in Eindhoven or Tilburg or at one of the commercial partners in several locations in Europe.

Job requirements

Candidates should:

  • Have a MSc. in Mathematics, Statistics, Computer Science, Computer Engineering, AI or a related discipline.
  • Have a strong interest in machine-learning and deep-learning.
  • Have excellent programming skills and be highly motivated, be rigorous and disciplined when developing algorithms and software according to high quality standards.
  • Have good technical understanding of the statistical models used in data science and machine learning;
  • Have knowledge of, or a willingness to familiarize themselves with, current research into machine learning for software engineering quality evaluation.
  • Have a commitment to develop algorithms that analyze Big Data from software-defined infrastructures as well as Big Code.
  • Be a fast learner, autonomous and creative, show dedication and be hard working.
  • Possess good communication capabilities and be an efficient team worker.
  • Be fluent in English, both spoken and written.

Job description

Please find the full job desciption on the website of TU/e

Information and application

Application can only be done through the online portal of TU/e (see button below). Applications via regular email will not be taken into consideration. 

Apply via TU/e

Do you want to do cool stuff that matters?

We do cool stuff that matters, with data. The Jheronimus Academy of Data Science (JADS) is a unique cooperation between Eindhoven University of Technology (TU/e) and Tilburg University (TiU). At JADS, we believe that data science can provide answers to society’s complex issues. We provide innovative educational programs, data science research, and support for business and society. With a team of lecturers, students, scientists and entrepreneurs – from a wide range of sectors and disciplines – we work on creating impact with data science. We do this by connecting people, sectors and industries: in the past 5 years we have been working with 300+ organizations on data-related projects. Our main drivers? Doing cool stuff that matters with data. Our location at the former monastery Mariënburg in Den Bosch houses a vibrant campus fully dedicated to data science.

At JADS, you work in an ambitious team of professionals to meet the challenges of tomorrow together. We do cool stuff, that matters. We provide talent opportunities for both scientific staff and support staff. JADS is a human-centered organization; we pay attention to your personal development and value a good work-life balance.

More about working at JADS

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