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The Signal Processing, Learning, and Computing (SPLC) Group at the Baltic Institute of Advanced Technology (BPTI) seeks a postdoctoral researcher in theoretical signal processing.
Job Profile
The successful candidate will be developing new computational methods for airborne object recognition in radar signals. Your work will include
There will also be possibilities to engage in other projects of the SPLC group or pursue your own ideas consistent with the group’s interests. Presenting research results in the form of scientific conference presentations and journal publications will be supported. Besides conducting scientific research, you will also have a chance to contribute to developing real-world systems with our industrial partners.
Requirements for the Candidate
Prior experience in radar signal processing is welcome but not required. A balanced experience in theoretical and computational topics is expected from the ideal candidate. However, people putting mathematical rigor in the first place are also very welcome to apply.
What We Offer
Application
Please send the following information to open.positions.splc@bpti.eu:
Applications will be reviewed on a rolling basis until the position is filled.
About Us
BPTI is a private, high-tech-oriented research institute established in Lithuania in 2008. We are driven by our mission to create value by providing R&D services for global security. Our core competencies in research and innovations lie in theoretical and applied machine learning and signal processing, integrated circuit design for radar and communication systems, cybersecurity solutions, and military UX/UI development. We believe that the origins of any technological breakthrough are rooted in fundamental research and, thus, dedicate a considerable part of our efforts to this dimension. We are a part of the official scientific research institution network of Lithuania.
The SPLC group at BPTI focuses on developing mathematical methods for extracting information from signals and other forms of data and implementing these methods numerically on computing platforms. In mathematical terms, our work includes solving various inverse problems of deterministic or stochastic nature. It builds on expertise in applied mathematics areas, such as numerical analysis, statistics, and mathematical optimization. We give equal emphasis to both the conceptual and practical aspects of our work.