Message from Alessandro Foi: The Signal and Image Restoration Group is part of the Laboratory of Signal Processing at Tampere University of Technology. The group research is dedicated to the characterization, transformation, and filtering of noise and other degradations for a variety of consumer, medical, and scientific imaging devices. The group develops theoretically grounded models, methods, and regularization priors for unsupervised processing of data from a diverse range of sensors, including direct, inverse, as well as computational imaging systems, with the ultimate goal of substantially improving the sensing/imaging quality and extending the applicability and efficiency of these devices. It has a strong scientific profile and is involved in national and international projects with both academic and industrial partners.
The Signal and Image Restoration Group is currently looking for motivated and talented postdoctoral and doctoral-student level researchers to contribute to ongoing research projects. The main problems to be investigated include image sensing and restoration at extremely low energy levels (with application to inverse problems in physics and medicine), and adaptive control of ultrafast broadband laser sources.
The positions are strongly research focused. Activities include conducting empirical research, theoretical analysis, algorithm design, software development and validation, reading and writing scientific articles, presentation of the research results at seminars and conferences in Finland and abroad, acquiring (or assisting in acquiring) further funding.
Candidates hired for Doctoral Student positions will work towards completion of a PhD degree under the supervision of the senior members of the research group.
Candidates should hold a master or doctoral degree in image processing, computer science and/or engineering, data science, applied mathematics, or related areas.
Candidates are also expected to have good skills in scientific programming (preferably Matlab, Python, and/or C), proficiency in English, both written and spoken.
The following qualities are appreciated:
* a strong background in linear algebra, statistical estimation, machine learning, and/or numerical optimization;
* experience working with real data;
* experience working with sensors and control systems.
Candidates at the postdoctoral level must have a demonstrated ability to carry out independent research in at least one of the following fields: signal and image processing, machines learning, multivariate statistics.
Information and application instructions:
Message from Masoumeh Dashti:
We are inviting applications for the following Research Fellow and PhD positions in ``Bayesian Inference and Approximations of High-Dimensional Network Models" at the University of Sussex, Mathematics Department:
Please don't hesitate to ask for any further information.