PhD in Graph Database Acceleration using AI Hardware

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.

With over 110 (assistant, associate and full) professors, almost 300 PhD and EngD students, about 1500 Bachelor students and 1000 Master students, the Department of Mathematics and Computer Science (M&CS) is the largest department of the TU/e. By performing top-level fundamental and applied research, and maintaining strong ties with industry, M&CS aims to contribute to science and innovation in and beyond the region.

Introduction

Are you passionate about bridging hardware acceleration and graph databases? Join us to develop groundbreaking self-healing Graph Neural Networks with Compute-in-Memory architectures that could revolutionize data processing efficiency.

Job Description

You will work on an innovative project at the intersection of database systems and hardware architectures, contributing to the EAISI Exploratory Multidisciplinary AI Research project SEAL. You will contribute to the Electronic Systems group and Databases group of TU Eindhoven, collaborating with experts in processor architectures, database systems, and machine learning.

The core challenge of this position is developing novel self-healing Graph Neural Network models optimized for efficient implementation on Compute-in-Memory architectures, with the goal of dramatically improving both processing time and energy efficiency for graph database operations.

Your research will involve:

• Designing new graph database structures using self-healing Graph Neural Networks
• Developing energy-efficient Compute-in-Memory architectures for GNN acceleration
• Creating and evaluating hardware prototypes with recent transistor technologies
• Publishing your findings in top-tier conferences and journals

This position offers you the opportunity to make significant contributions at the cutting edge of interdisciplinary research, with real-world applications that could transform database processing efficiency.

Job Requirements

• A master's degree in Computer Engineering, Electrical Engineering, Computer Science, or an equivalent university degree.
• A research-oriented attitude.
• Ability to work in an interdisciplinary team and interested in collaborating with industrial partners.
• Motivated to develop your teaching skills and coach students.
• Fluent in spoken and written English (C1 level).
• Strong background in at least one of the following: computer architecture, machine learning, or database systems.
• Experience with hardware description languages (VHDL/Verilog) and/or neural network frameworks.
• Proficiency in programming languages like C++ and SystemVerilog.
• Strong mathematical and analytical skills.

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. 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.
• 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. €2.901 max. €3.707).
• 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, on-campus children's day care 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.

Information

Do you recognize yourself in this profile and would you like to know more?
Please contact:

Manil Dev Gomony, Assistant Professor, Department of Electrical Engineering ([email protected])

Nikolay Yakovets, Assistant Professor, Department of Computer Science ([email protected])

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.

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.