Machine Learning for Signal Processing

Many applications generate large data sets from which information needs to be extracted. The emerging field of structured data science extends signal processing to data science. 

Context

Retrieving useful information out of large data sets is receiving an increasing amount of attention these days. Emerging applications like autonomous driving, the square kilometre array for radio astronomy, biomedical sensing systems, the internet-of-things with millions of users and sensors, all generate enormous amounts of data and it is not always clear how to gather, process, and analyze that data in an efficient and rigorous manner. Data science provides a solution to this problem. It basically yields a set of tools for data mining, data cleansing, machine learning and data analysis. 

While these tools can tackle a wide variety of problems, computer science approaches often ignore the structure that is present in the problem due to the physics. This structure could come from the prior knowledge of the model that generates the data (e.g., radio frequency channel models, biomedical signal models, diffusion models), or it could directly relate to the structure in the data (e.g., space-time, sparsity, network/graph data). Taking such structure into account will aid many of the existing data science tools, making them easier to interpret and simpler to implement. This field of structured data science is shaped by the nontrivial interplay between conventional signal processing and conventional data science. The goal is to illuminate and explore this interplay and apply it to the earlier mentioned applications.

Requirements

The opening for an Assistant Professor at TU Delft is intended to further develop this area. A background in statistical signal processing/modelling and the ability to apply this to data science/machine learning is required. Generally we search for candidates with a strong signal processing background complementary to the expertise that is already present in the CAS group. 

The candidate will also be involved in teaching and e.g. develop new courses on structured data science and machine learning for Electrical Engineering students.

While this position is defined as a tenure-track Assistant Professor position, excellently qualified but more senior researchers are also invited to apply.

Candidates should have (1) a PhD degree in Electrical Engineering or a closely related disciplne, with outstanding academic credentials, (2) several years of working experience as a Postdoctoral Researcher in an academic institution, and (3) the ambition to be a future scientific leader in the mentioned area.

Please announce your interest to Mrs. Minke van der Put (M.J.vanderPut@tudelft.nl) by submitting your CV, cover letter and contact details. Clearly indicate the related area of interest (i.e., structured data science), as this opening is part of a wider search for new faculty.

Contact Prof. Geert Leus for informal information.