Applied Signal Processing Systems

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.

Tenure-Track Faculty Position in Signal Processing 

The Electrical and Systems Engineering department at Washington University in St. Louis invites applications for multiple tenure-track faculty positions with an effective start date on or after July 1, 2025. Candidates should have earned a Ph.D. or equivalent degree in electrical engineering, systems engineering, computer engineering or a closely related discipline. Washington University is a highly-selective national research university with a strong tradition of research excellence. It is nationally known for its student body's exceptional quality and attractive campus, which borders residential neighborhoods and one of the nation’s largest urban parks. Many faculty walk or bike to work. St. Louis combines affordability with a vibrant metropolitan area, offering many cultural and entertainment opportunities.

The University’s strategic plan, released in 2022, seeks growth of top-tier research, scholarship, and creative practice with an emphasis on transdisciplinary and cross-school research. Included in this plan are foci related to applications in medicine, public health, infrastructure, and addressing pressing societal challenges. We seek both junior and senior applicants who will contribute to fundamental and applied research in signal processing and closely related areas. Examples include:

(I) Signal processing and deep learning

(II) Graph signal processing

(III) Audio, speech and image processing

(IV) Signal processing in neuroscience

(V) Statistical machine learning

Successful applicants will have a primary appointment in the department of Electrical and Systems Engineering with the possibility of joint appointments in other departments. The faculty member will be expected to teach undergraduate and graduate courses in electrical and systems engineering, participate in university service, and establish a thriving externally-funded research program. Faculty positions are open for all levels; appointment at a senior rank (associate and full professor) will be considered for exceptional candidates with a distinguished record of achievement in research and teaching.

Candidates should have earned a Ph.D. or equivalent degree in electrical engineering, systems engineering, computer engineering or a closely-related discipline.

Applications should include: (1) a cover letter that identifies the candidate’s three most significant publications and describes their interest in the position; (2) a curriculum vitae; (3) a research plan for the next five years that should not exceed three pages, and should highlight the problem(s) or set of questions to be investigated, the envisioned approach, a mentoring strategy, and the proposed funding sources; (4) a statement of teaching interests and philosophy (not exceeding 2 pages); (5) a statement describing contributions to and future plans for enhancing diversity (not exceeding 2 pages); and (6) a list of at least three references via the link provided at

https://apply.interfolio.com/157328

Priority will be given to completed applications (including submitted reference letters) received before December 15, 2024. However, applications will be accepted at any time and will be considered until the positions are filled. Washington University in St. Louis is committed to the principles and practices of equal employment opportunity and especially encourages applications by those underrepresented in their academic fields. It is the University’s policy to recruit, hire, train, and promote persons in all job titles without regard to race, color, age, religion, sex, sexual orientation, gender identity or expression, national origin, protected veteran status, disability, or genetic information. Verification of employment eligibility will be required upon employment.

Please visit UTSA job website for more details and to apply.

The University of Texas at San Antonio (UTSA), MATRIX AI Consortium, invites applications for the position of Full Professor / Associate Professor, to be appointed as a University of Texas System (UT System) Research Excellence Regents' Professor. Successful candidates will be part of a strategic cluster hiring initiative focused on Artificial Intelligence, with an anticipated start date in the Fall of the 2025-26 academic year.

The University of Texas System recently approved the creation of the Regents’ Research Excellence Program across its four Emerging Research Universities (ERUs), including UTSA. UT System has allocated $55 million across all four ERUs to fund the recruitment of research-active faculty to dramatically grow its national research prominence and federal funding opportunities. UTSA’s allocation from UT System translates to approximately 40 new faculty positions for new, mid- to senior-level faculty over the next several years who will add expertise in research areas that will enhance competitiveness, help solve societal needs, and advance the university’s capacity to meet UT System and state goals as outlined by the Texas Legislature.

UTSA is utilizing our Clustered & Connected Hiring Program (CCP), which is designed to recruit and hire some of the best and brightest minds of varying backgrounds and experiences in select fields to The University of Texas at San Antonio to join in efforts to address some of today’s most significant challenges.

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.

** PhD Opportunities in Centre for Doctoral Training in AI for Digital Media Inclusion
** Surrey Institute for People-Centred AI at the University of Surrey, UK, and
** StoryFutures at Royal Holloway University of London, UK

** Apply by 30 May 2024, for PhD cohort starting October 2024

URL: https://www.surrey.ac.uk/artificial-intelligence/cdt

The Centre for Doctoral Training (CDT) in AI for Digital Media Inclusion combines the world-leading expertise of the Surrey Institute for People-Centred AI at the University of Surrey, a pioneer in AI technologies for the creative industries (vision, audio, language, machine learning) and StoryFutures at Royal Holloway University of London, leader in creative production and audience experience (arts, psychology, user research, creative production).

Our vision is to deliver unique cross-disciplinary training embedded in real-world challenges and creative practice, and to address the industry need for people with responsible AI, inclusive design and creative skills. The CDT challenge-led training programme will foster a responsible AI-enabled inclusive media ecosystem with industry. By partnering with 50+ organisations, our challenge-led model will be co-designed and co-delivered with the creative industry to remove significant real-world barriers to media inclusion.

The overall learning objective of the CDT training programme is that all PhD researchers gain a cross-disciplinary understanding of fundamental AI science, inclusive design and creative industry practice, together with responsible AI research and innovation leadership, to lead the creation of future AI-enabled inclusive media.

The CDT training program will select PhD students who will work on challenge areas including Intelligent personalisation of media experiences for digital inclusion, and Generative AI for digital inclusion. Example projects related to audio include:

- Audio Generative AI from visuals as an alternative to Audio Description
- Audio orchestration for neurodivergent audiences using object-based media
- AUDItory Blending for Inclusive Listening Experiences (AUDIBLE)
- Foundational models for audio (including speech, music, sound effect) to texts in the wild
- Generative AI for natural language description of audio for the deaf and hearing impaired
- Generative AI with Creative Control, Explainability, and Accessibility
- Personalised audio editing with generative models
- Personalised subtitling for readers of different abilities
- Translation of auditory distance across alternate advanced audio formats

If you have any questions about the CDT, please contact Adrian Hilton or Polly Dalton.

For more information and to apply, visit:
https://www.surrey.ac.uk/artificial-intelligence/cdt

Application deadline: 30 May 2024

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Prof Mark D Plumbley
EPSRC Fellow in AI for Sound
Professor of Signal Processing
Centre for Vision, Speech and Signal Processing
University of Surrey, Guildford, Surrey, GU2 7XH, UK
Email: m.plumbley@surrey.ac.uk

Topic: Geometric Structure Adaptation of Wide-angle Photography

• PhD in computer science, electrical and computer engineering, or other related area, preferably awarded in the past three years.
• Have background on a relevant computer science area, notably in computer vision and computer graphics fields, demonstrated by a publication record in top-ranked conferences and/or journals.
• Have strong motivation to perform research in a rich and stimulating research group, as well as to advance state-of-the-art through the publication of results in international conferences and peer reviewed journals. 
• Be fluent in English, with good oral, technical writing and presenting skills. 
• Have good programming skills (Python, C/C++, etc.). 
• Well-known researchers will coordinate the research work with the selected candidate: Prof. João Ascenso and Prof. Paula Queluz. The candidate will join a dynamic team of Professors and PhD students where strong research and development activities in visual analysis and processing are carried out. 

Advanced driver assistance systems are key to enhancing road safety. One of the critical requirements for such systems is to reliably perceive the environment. The state-of-the-art sensors, however, are not ubiquitously deployed in driver assistance systems due to their high cost. On the other hand, simpler low-cost sensing solutions suffer from poor perception. 

In this project, you will address this gap by combining sensing capacities of the human driver and the driver assistance system, to develop sensing solutions that are both affordable and reliable. Your aim will be to develop signal processing algorithms and interfaces to incorporate driver in the sensing loop of automated driver assistance systems. Your work will leverage the unique cognitive abilities of humans controlling these systems to process complex signals and make informed real-time decisions. The project will lay the foundations for understanding how human interaction with signal processing systems impacts transparency and ethical considerations in deploying hybrid human-in-the-loop solutions.

In this project, you will be able to develop your skills in designing innovative human-in-the loop sensing solutions, rapid prototyping, and evaluation of your solutions in driving simulator experiments with human participants. You will work together with Dr. Nitin Myers from the Delft Center for Systems and Control, and Dr. Arkady Zgonnikov from the Department of Cognitive Robotics at TU Delft.

We are looking for candidates interested in developing deep learning algorithms for brain-related 2D/3D MRI or microscopy images. Possible topics include image registration, segmentation or the automatic tracking/tracing of neurons in large 3D image data. We also welcome new project proposals related to brain/neuron image data analysis.

Experience in biomedical image analysis is a plus, but not a requirement. This position can be a great opportunity to apply knowledge and expertise from computer vision and/or image processing to new problems in the biomedical field.

Our webpage can be found here: https://bia.riken.jp We are looking forward to hearing from you

Mendenhall Postdoctoral Fellowship Opportunity 21-20: Rapid, robust characterization of earthquake uncertainties to unlock advanced monitoring, forecasting, and research

Earthquake monitoring forms the foundation of earthquake forecasting and research.  Although overall earthquake monitoring capabilities have become increasingly sophisticated in the past decades, methods of uncertainty quantification, key to earthquake forecasting and other applications, have remained primitive.  Currently, uncertainties in fundamental earthquake source parameters, such as location and magnitude, are not standardized and are usually derived only from misfit within a particular assumed model (also known as “model errors”) or from ad hoc, outdated approximations. Characterizations like these ignore significant sources of uncertainty and bias (such as from discrepancies between different magnitude types or errors in the velocity model) and often dramatically underestimate the total uncertainty.  Current shortcomings in uncertainty quantification significantly impair impactful products that build upon earthquake monitoring and the associated catalogs, and perhaps less obviously, earthquake monitoring itself. 

We seek applicants with strong quantitative skills.  Experience in seismology and/or statistics highly beneficial.