Job description
The proliferation of Internet-connected and sensor-enabled technologies, including autonomous vehicles, wearables, smartphones, and other IoT devices, has resulted in distributed systems that generate vast quantities of data with a high velocity and volume. This abundance of data presents compelling opportunities for deep learning to solve a diverse array of complex tasks and challenges. The emerging field of federated learning investigates methods to leverage the wealth of data distributed across heterogeneous edge devices to collaboratively train models at scale. Though, there remain open research challenges regarding ensuring data privacy, non-stationary distributions, concept drift, scaling algorithms to large numbers of resource-constrained devices, and practical deployment considerations given real-world requirements.
To this end, we seek an excellent and highly motivated candidate for a Ph.D. position in the area of federated learning with a focus on developing data-centric approaches. The research topics include, but are not restricted to: dealing with multimodality, handling unlabelled data, incorporating human agency, ensuring fairness, adaptive personalization, robustness, and enhancing user-system interplay. For instance, a potential application area for federated learning is in personal health sensing using wearable devices. The digital devices, such as fitness trackers, smart watches, and other biosensors can continuously capture physiological signals like heart rate, activity levels, sleep, and more. They generate substantial amounts of data on a daily basis for each individual user. Federated learning techniques could enable collaborative training of deep learning models on most relevant data across users without compromising privacy.
This Ph.D. position provides the opportunity to advance the frontier of federated learning and distributed sensing systems. The candidate will be supervised by senior researchers and design experts in the Department of Industrial Design at Eindhoven University of Technology and will contribute to its vibrant research community with connections to interesting lines of research in health, mobility and sustainability.
Job requirements
- Master’s degree in Computer Science, Mathematics, Machine Learning or a related technical field.
- Strong interest in deep learning with a motivation to apply these techniques to problems in the healthcare domain.
- Ability to work independently and persistently tackle difficult research problems.
- Excellent analytical, problem-solving, and software engineering skills with prior experience implementing machine learning algorithms using well-known frameworks (e.g., PyTorch, TensorFlow, and Flower).
- Aspiration to achieve high-quality research contributions and publications in leading conferences and journals.
- Collaborative spirit and ability to work productively as part of a multidisciplinary team.
- Strong communication skills, including proficiency in written and spoken English and the ability to effectively present technical information to academic and non-expert audiences.
- Interest and ideally experience in design research methods to understand human needs, behaviors, and experiences. Willingness to incorporate user-centered approaches to tackling research problems and evaluating solutions.
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.
- 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 and application
About TU/e, Industrial Design and Future Everyday
You will be situated in the Future Everyday group, which investigates the everyday interactions between individual people and the highly interconnected technology that surrounds them. We measure, model, and design for the user experience when individuals interact with social-technological networks in their homes, at work, in transit, while doing sports, or going out.
TU/e is a leading international university specializing in Engineering Science & Technology. With high-quality education and research, TU/e ensures the progress of technical sciences and the development of technological innovations. TU/e is located in a highly industrialized region in the Netherlands, known as the ‘Brainport’. This region is internationally recognized as a top technology area with a special focus on the integration of design and technology. The department of Industrial Design at TU/e is internationally recognized for its scientific research on the design of systems with emerging technologies in a societal context. We excel at the acquisition and execution of projects where “integration of emerging technology into everyday life” and “application of technology in a societal context” play a major role. The Future Everyday research group investigates the everyday interactions between people and the highly interconnected technology that surrounds them.
General information about TU/e and the Industrial Design Department, candidates will find on https://www.tue.nl/en.
Information
Do you recognize yourself in this profile and would you like to know more?
Please contact the hiring manager dr. A. Saeed, assistant professor, email a.saeed[at]tue.nl.
Visit our website for more information about the application process or the conditions of employment. You can also contact HR-services, email HRservices.ID[at]tue.nl or +31 40 247 8827.
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. Applications submitted by email will not be processed. 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 and grades from MSc. and BSc.
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.