Signal Processing Theory and Methods

We have multiple open positions in the Distributed and Networked Control Systems (DNCS) group at the University of Cyprus, including PhD and Postdoc opportunities. We are seeking highly motivated individuals to join our research group who will contribute to cutting-edge research in control over communications and communications over control for cooperative autonomous systems. Specifically, our open (fully-funded) positions are:
      P1. Postdoc on “Distributed real-time, resource-efficient channel mapping and prediction”
      P2. Postdoc on “Information theoretic approaches for real-time estimation and control”
      P3. PhD on “Information theoretic approaches for real-time estimation and control”
      P4. PhD on “Model-based learning for joint control synthesis and communication in cooperative autonomous systems”

Why join us?

• Work alongside renowned researchers in a collaborative environment
• Access state-of-the-art facilities and equipment, including drones and mobile robots.
• Engage in high-impact research with opportunities for publication and collaboration with top institutions worldwide
• Become part of an international, friendly team with regular events (talks, visitors, etc) and networking opportunities

Successful Postdoc candidates

• Completed their PhD in a relevant discipline (such as electrical engineering, robotics, or computer science) within the last 5 years
• Academic achievements in control, robotics, and/or machine learning (e.g., journal papers in top-tier venues)
• Strong programming skills
• High level of commitment and initiative combined with creativity
• Excellent writing and communication skills in English for research publications and presentations

Successful PhD candidates

• Hold a master's degree in electrical/computer engineering, computer science, or related fields with excellent grades
• Strong proficiency in mathematical tools (e.g., linear algebra, graph theory, optimization). Background in control, path planning, or decision-making algorithms is a plus.
• Possess very good programming skills
• Proficiency in writing and speaking English

How to apply
Interested applicants should submit the following as a single PDF file:

• Letter of motivation (maximum 1 page in 10pt font size)
• CV with contact details
• Degree certificates and Transcripts (if not in Greek or English, a certified English translation)
• Contact details of at least two referees

Please send your application via email to the Director of the DNCS Group, Professor Themistoklis Charalambous (charalambous.themistoklis@ucy.ac.cy) with the subject title MINERVA2025-Application-P* (where * you insert the number of the position of interest from P1 to P4) by Monday, 31st of March 2025. For more information, please contact Professor Themistoklis Charalambous directly.

About the director of the group
Prof. Themistoklis Charalambous is currently a tenure track Assistant Professor at the University of Cyprus (UCY) and a Visiting Professor at FinEst Center for Smart Cities in Estonia and Aalto University in Finland (where he was serving as a tenured Associate Professor at the Department of Electrical Engineering and Automation, School of Electrical Engineering until August 2021). He received his BA (First Class Honours) and MEng (Distinction) in Electrical and Information Sciences from Trinity College, Cambridge University, in 2005. He completed his PhD studies in the Control Laboratory of the Engineering Department at Cambridge University. Following his PhD, he held research positions at Imperial College London, Royal Institute of Technology (KTH), and Chalmers University of Technology. In January 2017, he joined the Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University as a tenure-track Assistant Professor. In September 2018, he was nominated as a Research Fellow of the Academy of Finland, and in July 2020, he was promoted to tenured Associate Professor. In 2022, he was awarded the prestigious European Research Council (ERC) Consolidator Grant of €2,000,000 for 5 years for the project “eMergINg coopERatiVe Autonomous systems - information for control and estimation (MINERVA)”.

About the University of Cyprus
The University of Cyprus (UCY), with around 7.000 students, 113 laboratories, and 830 faculty and staff members, is the country’s leading public university and has established itself as a hub of academic excellence, research, and innovation since its founding in 1989. UCY is recognized for its strong research output, participating in major EU-funded projects such as Horizon 2020 and Horizon Europe, while consistently ranking among the top universities in Europe, particularly for research impact. Currently, UCY is ranked in the top 100 best young universities in the world according to the Times Higher Education (THE) Young University Rankings for universities less than 50 years old. Established in 2001, the Department of Electrical and Computer Engineering (ECE) at the University of Cyprus has rapidly developed into a dynamic hub where scientists and engineers from diverse disciplines collaborate to tackle complex scientific and technological challenges. The department’s research spans cutting-edge fields, including control, robotics, and autonomous systems; well-being and smart living environments; industrial electronics and informatics; and power systems and conversion. Demonstrating its commitment to excellence, the University of Cyprus has been ranked among the top 151-200 institutions worldwide for Electrical and Electronic Engineering and 101-150 for Automation and Control in the 2024 Academic Ranking of World Universities (Shanghai Rankings). This recognition reflects the department’s dedication to high-quality research, innovative teaching, and impactful outreach, solidifying its position as a leader in engineering education and research in the region.

Tampere University has several professor positions open related to AI and its applications, covering various areas of signal processing. The positions include a quite substantial starting package, covering funding for multiple research group members. Strong researchers are encouraged to apply! The deadline for applications is 9 March 2025. For more information about the positions, please visit this page.

Applications are invited for postdoctoral researcher positions in the general area of optimization and learning of network systems. Competitive financial supports will be provided.

Candidates with a clear interest in the general area of network systems are encouraged to apply.

Specific areas of research include:

• multi-agent optimization and learning
• game theory
• cooperative control

Clemson University is ranked 23rd among national public universities by U.S. News & World Report. It is described by students and faculty as an inclusive, student-centered community characterized by high academic standards, a culture of collaboration, school spirit, and a competitive drive to excel. Clemson is located on Lake Hartwell in the foothills of the Blue Ridge Mountains, an area of outstanding natural beauty and temperate climate. It is 30 miles from Greenville, SC, a vibrant and growing city which provides many opportunities for entertainment, culture, and fine dining.

Strong mathematical and analytic skills are desired. Candidates with a demonstrated track record in one or more of the previous area(s) will be preferred. Interested students should send a short resume, along with representative relevant publications, to yongqiw@clemson.edu

The Signal Processing Research Centre of Tampere University is looking for a tenure track-professor (assistant/associate/full) to join its team of world-class experts. Please see the full description and apply here.

Distributed learning algorithms based on methods such as least-mean square (LMS) or recursive least squares (RLS) were proposed not long ago, and allow sensor networks to collaborate to solve estimation and/or detection problems efficiently.  In addition, distributed versions of the Kalman filter were also proposed that allow optimal (or quasi-optimal) tracking of a parameter vector, under the constraints of linearity and Gaussianity.

Despite their superior performance, Kalman filters may not be adequate for use in sensor networks, due to their high computational cost  (the number of operations per sample needed grows with the cube of the number of parameters to be estimated), and also due to the need of a-priori knowledge of an accurate model for the parameter evolution.  We recently proved that it is possible to use combinations of adaptive filters to approximate the performance of Kalman filters with low computational cost (linear in the number of unknown parameters).  We also developed a new class of adaptive filters that allows near-optimal tracking with low computational cost for a larger class of models than possible with classical adaptive filters.

The goal of this work is to extend these results and to develop low-cost approximations to the Kalman filter that are robust against uncertainties in the model for the variation of the parameter vector to be estimated.  Due to the low complexity, this kind of algorithm would allow the implementation of algorithms with better tracking properties in sensor networks, and the robustness would allow the application to a class of problems in which performance guarantees are important, such as distributed control (cooperative autonomous systems, for example).

Candidates with a strong background in Signal Processing and Automatic Control or Telecommunications are encouraged to apply.  The position will be at the Electronic Systems Engineering Department at the University of São Paulo, São Paulo, Brazil, and may extend to up to four years.  The salary will be R$ 9,047.40 (tax-free), plus 10% for expenses.  Funding for relocation to São Paulo is also available, including for spouses.  

            Applications should be sent till Jan. 15, 2024 by e-mail to vitnasci@usp.br, with a short CV following the guidelines found here: 

https://fapesp.br/6351/instructions-for-the-elaboration-of-a-curricular-summary

The Department of Information and Communications Engineering is looking for outstanding

Postdoctoral Researchers in the area of Personalized Online Machine Learning for Wireless Networks

Are you an ambitious and talented researcher seeking to push the boundaries of machine learning and wireless communications? Do you want to be part of an innovative team working on cutting-edge projects that have real-world impact? If so, we invite you to apply for our prestigious three-year postdoctoral position at the Department of Information and Communications Engineering (DICE), Aalto University, Helsinki, Finland. 

Your role and goals

We are specifically looking for candidates with a deep passion for research and who demonstrate the potential to excel in various cutting-edge research areas related to statistical learning for emerging communications systems. These areas encompass meta-learning for heterogeneous systems, networked federated learning, privacy-preserving machine learning, Byzantine-resilient learning, and robust resource-efficient distributed optimization. As a postdoctoral researcher in PLEDGE, you will lead pioneering research at Aalto University's Department of Information and Communications Engineering. Your primary focus will be developing innovative algorithms and theories for reliable learning in resource-constrained networks with irregular and unstructured streaming data. You will be actively involved in creating decentralized personalized learning solutions in multi-agent wireless networks, such as the internet of things (IoT) and cyber-physical systems (CPS). Your work will be instrumental in advancing the digital transformation of industries and societies, contributing to solutions for various real-world challenges.

Your experience and ambitions

We seek a highly motivated and skilled researcher with a solid background in signal processing, statistical machine learning, optimization, wireless communications, or applied mathematics. Your expertise should be demonstrated through high-quality research publications, including at least one IEEE Transactions paper. Strong mathematical and programming skills, as well as proficiency in English, are essential. Your collaborative and proactive nature and excellent communication skills will be key to successfully contributing to the team. In summary, the ideal candidate has:

• A Ph.D. degree in Information and Communications Engineering, Electrical Engineering, Computer Science, or related fields.
• A strong research background with expertise in one or more of the following areas: signal processing, statistical machine learning, optimization, wireless communications, or applied mathematics.
• Proven track record of academic excellence demonstrated through high-quality research publications, including at least one IEEE Transactions paper.
• Solid programming skills and experience with relevant tools and libraries.
• A collaborative and proactive attitude with excellent communication skills
• Fluency in written and spoken English.

Don't miss out on this exciting opportunity – apply now! The best-qualified candidates will be invited for an interview.

Apply now

For more information about the position and application submission, please visit this page.

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

• Performing theoretical analysis of relevant structural feature recoverability from Doppler signatures,

• Designing new specialized approaches to object recognition,

• Creating numerical algorithms for efficient implementations of these approaches on computing platforms,

• Carrying out real-world data analysis and model simulations.

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

• Doctoral degree in Applied Mathematics, Computer Science, Electronics & Electrical Engineering, Physics, or a related field

• Proven skills and experience in successfully designing and carrying out research projects

• Either theoretical knowledge or working experience in a significant subset of the following areas:

  • Numerical analysis,

  • Statistical inference,

  • Signal processing,

  • Mathematical optimization,

  • Machine learning,

  • Scientific computing.

• Proficiency in at least one high-level programming language and development environment suitable for numerical computing, data analysis, and visualization (e.g., MATLAB, Python, Julia) demonstrated via routine use in research projects

• Fluency in written and spoken English

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

• 3800 – 4500 Eur / month (gross) salary depending on the actual competencies

• Possibility of qualifying for a permanent position after a 1-year fixed-term contract

• Possibility of focussing on quality research instead of chasing performance metrics

• Close ties with industry to turn your research results into real-world solutions

Application

Please send the following information to open.positions.splc@bpti.eu:

• Cover letter briefly describing your motivation for choosing this position in connection to your interests and previous experience,

• Curriculum Vitae,

• A list of short summaries of your previous research projects describing the problem, the solution, the conclusion, and your contribution.

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.

The Signal Processing, Learning, and Computing (SPLC) Group at the Baltic Institute of Advanced Technology (BPTI) seeks a postdoctoral researcher in theoretical and applied signal processing.

Job Profile

The successful candidate will develop new computational methods for airborne object recognition in radar signals. At the technical level, the work will involve

• Performing theoretical analysis of relevant structural feature recoverability from Doppler signatures,

• Designing new specialized approaches to object recognition,

• Creating numerical algorithms for efficient implementations of object recognition on computing platforms,

• Carrying out real-world data analysis and model simulations.

There will also be possibilities to engage in other projects curated by 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

• Doctoral degree in Applied Mathematics, Computer Science, Electronics & Electrical Engineering, Physics, or a related field

• Proven skills and experience in successfully designing and carrying out research projects

• Either theoretical knowledge or working experience in a significant subset of the following areas:

  • Numerical analysis,

  • Statistical inference,

  • Signal processing,

  • Mathematical optimization,

  • Machine learning,

  • Scientific computing.

• Proficiency in at least one high-level programming language and development environment suitable for numerical computing, data analysis, and visualization (e.g., MATLAB, Python, Julia) demonstrated via routine use in research projects

• Fluency in written and spoken English

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

• 3500 – 4500 Eur / month (gross) salary depending on the actual competencies

• Possibility of qualifying for a permanent position after a 1-year fixed-term contract

• Focussing on quality research instead of chasing dubious performance metrics

• Close ties with industry to turn your research results into real-world solutions

Application

Please send the following information to open.positions.splc@bpti.eu compiled to a single pdf file:

• Cover letter briefly describing your motivation for choosing this position in connection to your interests and previous experience,

• Curriculum Vitae,

• A list of short summaries of your previous research projects describing the problem, the solution, the conclusion, and your contribution.

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 revolves around 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 the practical aspects of our work.

About the job

The Department of Electronic Systems (IES) has a vacancy for a Postdoctoral Researcher in statistical machine learning and distributed signal processing with applications in IoT. The successful candidate will be offered a three-year (3 years) appointment.

The position is linked to IoT@NTNU, a hub for IoT research at the Faculty of Information Technology and Electrical Engineering (IE), coordinated by IES. The project deals with big data, the internet of things (IoT), and artificial intelligence as critical enablers of IoT. In IoT, large volumes of data, often even personal data, are constantly gathered by numerous geographically dispersed sensors and devices, opening up a vast number of application areas that call for new approaches to data processing and inference. For example, concentrating the data at a central processing hub might be unfeasible due to constraints on the energy budgets of the data-collecting sensors/devices, the integrity of data holders, or the capacity of the communication channels. Thus, robust and privacy-preserving distributed or graph-based data processing over networks of machines/agents will be essential for performing data processing in future IoT-based applications. Examples of application areas of interest include but are not limited to, sensor fusion, health, smart cities, Industry 4.0, and environmental monitoring.

The postdoctoral research fellow will be affiliated with the IoT@NTNU and the Norwegian Open AI lab and collaborate with leading research scientists from international partner institutions. In addition, the hired candidate is to conduct research and possibly guide other students associated with the team. Therefore, preference will be given to candidates who can work independently and have a strong potential to build competence in advanced signal processing and machine learning methods with applications in IoT. 

We search for candidates interested in these interdisciplinary tasks, and those with the best qualifications will be invited for an interview. 

Salary and conditions

As a Postdoctoral Fellow (code 1352) you are normally paid from gross NOK 563 500 per annum before tax, depending on qualifications and seniority. From the salary, 2% is deducted as a contribution to the Norwegian Public Service Pension Fund.

The period of employment is three (3) years.

The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants, and the acts relating to Control of the Export of Strategic Goods, Services and Technology. Candidates who by assessment of the application and attachment are seen to conflict with the criteria in the latter law will be prohibited from recruitment to NTNU.

About the application 

For more information and application submission, please visit the following link:

Postdoctoral Fellow in Signal Processing and Machine Learning for Emerging IoT Applications (241689) | NTNU - Norwegian University of Science and Technology (jobbnorge.no)

We are looking for candidates with a strong background in statistical signal processing, information theory, and good programming skills in Python and/or Matlab. Doctoral and postdoctoral candidates should have a master’s, and respectively Ph.D., degree preferably in signal processing, mathematics, data-science or related fields with a strong quantitative orientation. 

The successful candidates will develop the underpinning methods and algorithms required for autonomous distributed sensor management and fusion in challenging environments. The project will deliver key advances in intelligent sensing to enable continuous and adaptive surveillance in dynamic environments. Due to the advent of the Internet-of-Things and other extensive sensor networks, algorithms that judiciously manage the communication, sensing, and energy resources of such networks are crucial for efficient inference under various limitation and/or availability constraints for these resources. 

The project will involve the proposal of metrics for quantifying the information perceived by different sensors on multiple stochastic processes. Subsequently, these metrics will guide the development of algorithms for sequentially estimating the state of these processes, fuse information from heterogeneous sensors, and allocate resources based on information-theoretic criteria. These resulting algorithms will be applied to multiple target tracking with sensor networks. Building on recent developments by the investigators in multi-target tracking and distributed sensor fusion, this work programme will develop methods based on point process theory, which is designed to accommodate uncertainty in the states of individual targets and the number of targets. Information-theoretic metrics tailored for point processes will be proposed as well as optimization methods that employ these metrics in order to allocate sensor resources and refine the knowledge of the scene. 

For an informal discussion to find out more about the role please contact Professor Daniel Clark at daniel.clark@soton.ac.uk and Dr Augustin Saucan at Telecom SudParis augustin.saucan@telecom-sudparis.eu.

Doctoral applications should include (i) a curriculum vitae, (ii) a transcript of completed courses and grades (iii) a letter of motivation, and (iv) names and contact details of three referees. Post-doctoral applications should include only elements (i), (iii), and (iv) from the previous list. Candidates should send all application material in a single pdf or zip file to daniel.clark@telecom-sudparis.eu