PhD Position Split Learning over Distributed Heterogeneous Devices

PhD Position in Split Learning over Distributed Heterogeneous Devices.

Job description

Are you interested in distributed machine learning and how it can be efficiently deployed on heterogeneous devices? Do you want to contribute to the next generation of split learning techniques for scalable and efficient AI systems? Delft University of Technology (TU Delft) invites applications for a PhD position on Split Learning over Distributed Heterogeneous Devices as part of an international research collaboration.

About the Position

Modern machine learning applications often require models to be deployed across resource-constrained and heterogeneous devices, such as embedded systems, IoT devices, and edge computing platforms. Split learning is an emerging paradigm that enables distributed training by dividing neural network computations across multiple devices. This PhD project focuses on advancing split learning by optimizing how neural network models are partitioned and processed across diverse devices.

As part of the ANT MSCA Doctoral School, you’ll collaborate with top international research institutions and industry leaders, including NXP, ABB, Philips, IMEC. Enjoy a highly competitive salary, access to a leading-edge lab with high-end research facilities, and a tailored soft-skills program designed to support your career development.

You’ll be joining an international team exploring groundbreaking solutions for embedded AI systems. Here, you’ll tackle exciting challenges in how to designa deploy embedded AI alogorithm for small devices, building on your strengths—whether they lie in both theory and hands-on skills.

This position also includes two unique research visits:

           •  5 months visit to CSEM to work on model splitting with early exit on distributed devices

          •   4 months visit to A5 to work on Integration of dynamic sparse training

Your home base will be the Embedded Systems group at TU Delft, where you’ll be supervised by Dr. Qing Wang, co-founder of TU Delft's Embedded AI lab and project coordinator of ANT. As a member of this dynamic and dedicated research group, you will collaborate closely with academic staff, fellow PhD candidates, and postdoctoral researchers, all committed to advancing the field of network science. Our team fosters an environment of open discussion, knowledge exchange, and regular collaboration to explore complex networks across technological, biological, and social domains. Throughout your PhD journey, you will also receive comprehensive training to support your development as a researcher.

Job requirements

Required expertise:

We are looking for candidates with a background in at least one of the following domains in the context of embedded systems and AI:

•  Tiny Machine Learning
•  Distributed learning / federated learning
•  A solid hands-on experience of embedded systems

General requirements:

• Good track record in Master's and Bachelor's degrees
• Strong analytical or implementation skills
• Strong programming skills in one or more of the following languages:  Rust, MATLAB, Python
• Good command of the English language (written and spoken)

Conditions of international mobility of researchers:

Researchers are required to undertake trans-national mobility (i.e., move from one country to another) when taking up the appointment. At the time of selection by the TU Delft, the candidate must not have resided or carried out their main activity (work, studies, etc.) in the Netherlands for more than 12 months in the 3 years immediately prior to the recruitment. Short stays, such as holidays, are not taken into account.

TU Delft (Delft University of Technology) 

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

Faculty Electrical Engineering, Mathematics and Computer Science 

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.

Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.

Conditions of employment 
Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met. 

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2901 per month in the first year to € 3707 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills. 

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.  

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.  

Additional information
If you would like more information about this vacancy or the selection procedure, please contact Dr. Qing Wang, via qing.wang@tudelft.nl.

Application procedure
Are you interested in this vacancy? Please apply no later than April 13, 2025 via the application button and upload your application in one PDF containing:

1. A cover letter in which you explicitly state your topic of interest, the research plan, and why you find yourself a suitable candidate for this topic (max. 800 words).

2. Resume/CV including:

                • The applicant's educational and research background,

                • Professional skills,

                • List of publications, and

                • Two reference letters

3.            Copies of your BSc and MSc degrees and transcripts.

4.            Names and contact information of at least three relevant references.   

Applications will be evaluated as they come in, so please apply as soon as possible.

You can address your application to Dr. Qing Wang.

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements. 

Please note:

• You can apply online. We will not process applications sent by email and/or post. 

• A pre-employment screening can be part of the selection procedure.
• For the final candidates, a knowledge security check will be part of the application procedure. For more information on this check, please consult Chapter 8 of the National Knowledge Security Guidelines. We carry out this check on the basis of legitimate interest.
• Please do not contact us for unsolicited services.