Post-doctoral researcher in Machine Learning-Based Signal Decomposition

at  Maastricht University

Are you thrilled by the possibility of advancing traditional signal decomposition methods by integrating artificial neural networks for increased accuracy and tensor-based methods for improved efficiency? Then apply for this position as a post-doc researcher in Machine Learning-Based Signal Decomposition at the Department of Advanced Computing Sciences (DACS), part of the Faculty of Science and Engineering at Maastricht University.
The successful candidate will design new versatile methods for data-driven and adaptive decomposition of nonlinear and nonstationary signals, and analyze their performance in various domains like Engineering (e.g., fault detection), Physics (e.g., gravitational wave analysis), and Medicine (e.g., electrocardiographic signal analysis).
The position is embedded in the Systems and Control research group of DACS.

JOB DESCRIPTION

You will conduct research on data-driven decomposition of signals. More specifically, you will work on advancing the theoretical background of traditional techniques, and integrating those with both deep learning frameworks and tensor-based decomposition approaches. You will start by working on developing methods for decomposing univariate signals, followed by extending your findings to methods for decomposing multivariate signals. The final goal is to develop new flexible and versatile methods for decomposition of (multivariate) signals in physically meaningful components.

Your tasks will include:

• Perform scientific research in machine learning-based data-driven signal decomposition;
• Publish results at top-tier (international) conferences and in international journals;
• Present the results in internal research group meetings as well as national and international scientific conferences;
• Assist with educational tasks (e.g., assist labs, supervise bachelor and master students, PhD students, and internships);
• Participate actively in the activities of the Systems and Control research group such as grant acquisition and event organization.

We encourage collaboration and you will also benefit from a supportive local research community as well as a strong industry and research network.

REQUIREMENTS

• PhD (completed, or to be completed shortly) in Signal Processing, Machine Learning / Deep Learning, Applied Mathematics, Artificial Intelligence, or a related field.
• Demonstrated (e.g., through publications, code, projects, etc.) interest and experience with the field of signal processing, and at least one of the following fields: signal decomposition, machine learning / deep learning, tensor decomposition.
• Knowledge of at least one of the following techniques and interest in developing skills in the other two:
• Traditional decomposition techniques like Empirical Mode or Variational Mode Decomposition, Wavelet Decomposition, Principal and Independent Component Analysis.
• Machine learning and deep learning frameworks.
• Tensor-based methods for signal processing or machine learning decomposition (e.g., canonical polyadic decomposition, multilinear singular value decomposition, and tensor trains).
• Experience in programming (preferably in Python and Matlab).
• Proficiency in English (oral and written).
• Excellent communication skills, and ability to collaborate in a multi-disciplinary and team-oriented research environment.

MAASTRICHT UNIVERSITY

Why work at Maastricht University?
At Maastricht University (UM), everything revolves around the future. The future of our students, as we work to equip them with a solid, broad-based foundation for the rest of their lives. And the future of society, as we seek solutions through our research to issues from all around the world. Our six faculties combined provide a comprehensive package of study programmes and research.
In our teaching, we use the Problem-Based Learning (PBL) method. Students work in small groups, looking for solutions to problems themselves. By discussing issues and working together to draw conclusions, formulate answers and present them to their peers, students develop essential skills for their future careers.
With over 22,300 students and more than 5,000 employees from all over the world, UM is home to a vibrant and inspiring international community.
Are you drawn to an international setting focused on education, science and scholarship? Are you keen to contribute however your skills and qualities allow? Our door is open to you! As a young European university, we value your talent and look forward to creating the future together.

• Perform scientific research in machine learning-based data-driven signal decomposition;
• Publish results at top-tier (international) conferences and in international journals;
• Present the results in internal research group meetings as well as national and international scientific conferences;
• Assist with educational tasks (e.g., assist labs, supervise bachelor and master students, PhD students, and internships);
• Participate actively in the activities of the Systems and Control research group such as grant acquisition and event organization