Skip to main content

Image, Video and Multidimensional Signal Processing

IVMSP

Assistant/Associate/Full Professor in Computing Science (Fundamental and Applied AI)

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.

Read more

Tenure-Track Faculty Position in Signal Processing

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.

Read more

Professor

The School of Engineering & Applied Science (SEAS) at the University of Virginia (UVa) seeks candidates for a tenure-eligible or tenured position in the Department of Electrical and Computer Engineering. The primary responsibilities for this position include research, teaching, and service to the department, university, and professional community. The appointment rank and compensation will be commensurate with experience and qualifications. 

The search is in the general area of neuroimaging, brain function and connectivity, and artificial intelligence, with applications to neuroscience and/or neuro-degenerative disorders. The school is especially interested in candidates who are interested in developing technologies that will enable a comprehensive understanding of the brain. Strategic integration of computational methods such as machine learning, signal processing, network theory, and a focus on application to neurological disorders including autism and Alzheimer’s disease, is desirable.

Example research areas include, but are not limited to

  • Neuroimaging
  • Investigation of brain function and connectivity at multiple scales
  • Brain machine interfaces and neural signal processing
  • Neuromodulation and stimulation
  • Neuroinformatics

The Electrical and Computer Engineering (ECE) Department at the University of Virginia (UVA offers a vibrant environment for interdisciplinary research and collaboration, with strengths in areas such as machine learning, imaging, cyber-physical systems, embedded systems, communication networks, and energy systems. ECE at UVA emphasizes both foundational and applied research, preparing students for leadership in industry, academia, and government. Faculty members benefit from access to cutting-edge facilities and are encouraged to engage in research that addresses societal challenges. The close proximity with the School of Medicine offers rich opportunities for collaborations in the areas of Radiology, Neurology and Neuroscience, and Neurosurgery. Other collaborative opportunities include Biomedical Engineering, Psychology, and School of Data Science.

The University of Virginia's 2030 plan recognizes the Brain and Neuroscience as a major societal challenge and an opportunity for multidisciplinary work that draws on our existing strengths. In partnership the Provost and the deans of various schools are making multiple coordinated faculty recruitments to strengthen the research community focusing on Brain and Neuroscience across the University. Recruits will receive support from the Provost and from their school and will participate in the Brain and Neuroscience Initiative.  This is part of a major Grand Challenges research investment of over $50M in Brain and Neuroscience.

This position is based in Charlottesville at our principal location.  UVA is a highly selective undergraduate and graduate institution that annually ranks as one of the premiere public universities in the United States, with one of the highest graduation rates in the nation. UVA is situated in Charlottesville, Virginia, a picturesque and vibrant small city consistently recognized as one of the nation's top places to reside. UVA's location offers proximity to Washington D.C., enriching opportunities for collaboration and engagement with numerous federal organizations. More information about the city, the school, faculty benefits and other topics can be found at https://hr.virginia.edu/careers-uva/why-uva.

Qualifications

Candidates must have received a doctorate or equivalent in electrical engineering, computer science, biomedical engineering or related areas by the start of their appointment. Evidence of a commitment to high-impact scholarship, funded research, undergraduate- and graduate-level teaching and advising excellence, professional and university service, and mentoring are expected.

In conjunction with these positions, senior graduate students are eligible and encouraged to consider the UVA Engineering Rising Scholars program. This program is designed to encourage early-career scholars to pursue a career in academia by supporting their postdoctoral work before beginning in a tenure-track position at the University of Virginia. Detailed information and application instructions are available at https://engineering.virginia.edu/rising-scholars-postdoctoral-program.

Application Instructions

Apply for this position in Interfolio. Provide the following in PDF format: 

  • Cover letter that summarizes your areas of research/scholarship, and areas of potential collaboration at the University of Virginia. To help us organize our review of applications, please also specifically list your primary areas of research in boldface at the top of your letter   
  • Curriculum vitae  
  • A statement describing your current research, future directions, and broader impacts;  
  • A statement describing your teaching and mentoring practices, especially in regard to a residential learning environment marked by the free and collegial exchange of ideas; 
  • A statement describing demonstrated contributions to fostering inclusive practices that create climates in which all stakeholders can achieve their maximum potential (please focus on skills and experience, not beliefs and opinions) 
  • A single file that includes two research papers that best represent your work

You will also request 3-5 references directly in Interfolio by providing names and contact information in the application. These reference requests will be generated immediately once you submit your application.

Review of applications will begin on November 1, 2024 and will continue until the position is filled. The University will perform background checks on all new faculty hires prior to making a final offer of employment.  

For questions about these positions, please contact Mathews Jacob, Professor, Electrical and Computer Engineering at mjacob@virginia.edu

Read more

Two Post Doctoral Researchers and One PhD Student in Advanced Medical Image Analysis

Project Description

We are glad to announce the launch of a new research project based on the collaboration between the Mathematics and Data Science (MADS) research group at Vrije Universiteit Brussel (VUB) and the Centre for Reproductive Medicine at UZ Brussel (Brussels IVF). This project aims at helping the field of assisted reproductive technology (ART) by developing innovative AI-driven frameworks for the analysis of high-dimensional oocyte/embryo images. By integrating advanced deep learning and mathematical modeling, we seek to investigate, understand and potentially improve decision-making in ART procedures. The ultimate objective of this interdisciplinary research is to push the boundaries of current reproductive treatment, potentially offering new insights and tools for clinicians.

Open Positions

We are opening the following research positions in Digital Mathematics (DIMA), a research group chaired by Prof. Ann Dooms from MADS, VUB.

1. Post-doctoral Researchers (2 vacancies)

  • Focus Area: Advanced deep learning and machine intelligence for medical image analysis.
  • Duration: Full-time position for 2 years (with possibility for extending to 30 month). Starting from 1stSeptember 2024.
  • Key Responsibilities:
  • Conceptualize, develop and implement deep learning and mathematical modeling algorithms for analyzing high-dimensional medical images.
  • Collaborate with embryologists and clinicians to integrate biological motivations into AI models.
  • Publish research findings in high-impact journals and present at conferences.
    • Requirements:
    • PhD in Applied Mathematics, Computer Science, Electrical/Electronic/Information Engineering, or related fields.
    • Strong background in deep learning, machine learning, computer vision and image processing.
    • Proven track record of publications in top-tier conferences and journals.
    • Excellent programming skills in Python/MATLAB and rich experiences with deep learning frameworks (e.g., PyTorch).
    • English as official working language. 

2. Doctoral Candidate (1 position)

  • Focus Area: Mathematical modeling and machine learning for image analysis.
  • Duration: Full-time for 3 years (with possibility for extending to 4 years). Starting from 1st August 2024. 
  • Key Responsibilities:
    • Develop mathematical models to assist/enhance AI-driven (e.g., deep learning based) image analysis.
    • Work closely with embryologists and post-doctoral researchers to integrate these models into the overall framework.
    • Data collection, preprocessing, and annotation.
    • Contribute to writing research papers and project reports.
    • Obtain a PhD diploma following the regulations of VUB.
  • Requirements:
    • Master's degree in (Applied) Mathematics, Computer Science, Electronic and Information Engineering, or related fields.
    • Strong analytical and problem-solving skills, being able to conduct independent research and development with strong self-motivation.
    • Experiences with mathematical modeling, machine learning and computer vision.
    • Proficiency in programming languages such as Python or MATLAB.
    • English as official working language.

How to Apply

If you are a highly motivated individual with a passion for advancing medical technology through AI and mathematical modeling, we encourage you to apply. Please send your CV and a cover letter detailing your research experience and interests to Prof. Ann Dooms (Ann.Dooms@vub.be) and Prof. Tan Lu (Tan.Lu@vub.be). 

All applications must be sent before 1st July 2024.

Read more

Two Post Doctoral Researchers and One PhD Student in Advanced Medical Image Analysis

Project Description

We are glad to announce the launch of a new research project based on the collaboration between the Mathematics and Data Science (MADS) research group at Vrije Universiteit Brussel (VUB) and the Centre for Reproductive Medicine at UZ Brussel (Brussels IVF). This project aims at helping the field of assisted reproductive technology (ART) by developing innovative AI-driven frameworks for the analysis of high-dimensional oocyte/embryo images. By integrating advanced deep learning and mathematical modeling, we seek to investigate, understand and potentially improve decision-making in ART procedures. The ultimate objective of this interdisciplinary research is to push the boundaries of current reproductive treatment, potentially offering new insights and tools for clinicians.

Open Positions

We are opening the following research positions in Digital Mathematics (DIMA), a research group chaired by Prof. Ann Dooms from MADS, VUB.

1. Post-doctoral Researchers (2 vacancies)

  • Focus Area: Advanced deep learning and machine intelligence for medical image analysis.
  • Duration: Full-time position for 2 years (with possibility for extending to 30 month). Starting from 1stSeptember 2024.
  • Key Responsibilities:
  • Conceptualize, develop and implement deep learning and mathematical modeling algorithms for analyzing high-dimensional medical images.
  • Collaborate with embryologists and clinicians to integrate biological motivations into AI models.
  • Publish research findings in high-impact journals and present at conferences.
    • Requirements:
    • PhD in Applied Mathematics, Computer Science, Electrical/Electronic/Information Engineering, or related fields.
    • Strong background in deep learning, machine learning, computer vision and image processing.
    • Proven track record of publications in top-tier conferences and journals.
    • Excellent programming skills in Python/MATLAB and rich experiences with deep learning frameworks (e.g., PyTorch).
    • English as official working language. 

2. Doctoral Candidate (1 position)

  • Focus Area: Mathematical modeling and machine learning for image analysis.
  • Duration: Full-time for 3 years (with possibility for extending to 4 years). Starting from 1st August 2024. 
  • Key Responsibilities:
    • Develop mathematical models to assist/enhance AI-driven (e.g., deep learning based) image analysis.
    • Work closely with embryologists and post-doctoral researchers to integrate these models into the overall framework.
    • Data collection, preprocessing, and annotation.
    • Contribute to writing research papers and project reports.
    • Obtain a PhD diploma following the regulations of VUB.
  • Requirements:
    • Master's degree in (Applied) Mathematics, Computer Science, Electronic and Information Engineering, or related fields.
    • Strong analytical and problem-solving skills, being able to conduct independent research and development with strong self-motivation.
    • Experiences with mathematical modeling, machine learning and computer vision.
    • Proficiency in programming languages such as Python or MATLAB.
    • English as official working language.

How to Apply

If you are a highly motivated individual with a passion for advancing medical technology through AI and mathematical modeling, we encourage you to apply. Please send your CV and a cover letter detailing your research experience and interests to Prof. Ann Dooms (Ann.Dooms@vub.be) and Prof. Tan Lu (Tan.Lu@vub.be). 

All applications must be sent before 1st July 2024.

Read more

PhD Opportunities in AI for Digital Media Inclusion (Deadline 30 May 2024)

** 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

--

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

 

Read more

Postdoctoral Position in Computational Imaging

Topic: Geometric Structure Adaptation of Wide-angle Photography

Location: Instituto de Telecomunicações, Instituto Superior Técnico, University of Lisbon, Portugal   Project: Nowadays, smartphones come with a wide variety of cameras and sensors, each with a distinct function to improve the overall quality of images and enable different functionalities. These camera arrays and sensors include a primary camera with high resolution and best overall image quality, and often a wide-angle camera to provide an expanded field of view, allowing users to capture more in a single shot. This is excellent for landscape photography, architectural shots, group photos, and creative perspectives that emphasize the vastness of a visual scene. While wide-angle photography is rather powerful to capture a large field of view, it often introduces annoying geometric distortions. For example, objects closer to the camera may appear disproportionately larger than those in the background, leading to unnatural-looking images. Moreover, landscape and architectural photos obtained from wide-angle cameras often suffer from geometric distortions, such as perspective distortions, where objects near the edges of the image appear stretched or warped as well as curved or bent straight lines. Also, there should be certain consideration on captured image aesthetic while preserving the special relationships on modification. The focus of this project is on the development of efficient solutions that mitigate some of the challenges identified above.  The research work will be developed in the context of a research project with a well-known company.
Requirements: The candidates must fulfill the following conditions: 
  • 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. 
Research grant: The research grant is associated with a 1.5-year full-time contract. The research grant consists of a stipend of approx. 28000€/year net (after taxes).  To apply, please submit your application by sending an email to joao.ascenso@lx.it.pt and paula.queluz@lx.it.pt with the following documents:  1. Detailed curriculum vitae with transcripts (mandatory)
2. A motivation letter (research statement) explaining your interest in the position (mandatory)
3. Recommendation letter(s), especially from your PhD advisor or a list of individuals with contact information. 
Note that if the above documents are not received, your application may not be considered. Applications shall be received until 30/03/2024. Selected candidates will be submitted to one or more interviews. For any clarifications, please contact Prof. João Ascenso (joao.ascenso@lx.it.pt) and Prof. Paula Queluz (paula.queluz@lx.it.pt).

Read more

PhD Position in Multimedia Signal Processing at University of Lisbon

Location: Instituto de Telecomunicações, Instituto Superior Técnico, University of Lisbon, Portugal

Project title: Event-based Imaging
Project description: Event-based imaging, also known as neuromorphic imaging, is a recent visual information paradigm that relies on novel sensing and computing techniques that mimic how biological systems acquire and process visual information. In this paradigm, visual sensors do not capture and transmit images/frames at fixed time intervals, but rather operate on a different principle: individual pixels asynchronously respond to changes in the amount of incident light, resulting in a stream of asynchronous events. Therefore, the obtained visual data stream is sparse which makes it suitable for scenarios where very high temporal resolutions are desirable, notably in the acquisition of fast and dynamic scenes with high accuracy and low latency. Moreover, event-based imaging can efficiently handle uncontrolled lighting conditions (e.g. high dynamic range) and low-power consumption. This new visual information paradigm may therefore potentiate several advantages in many applications, such as in industrial automation, visual surveillance, augmented reality, automotive and mobile environments, drones and other applications which require fast response, high-dynamic range or low-power consumption. 

The research work will be developed in the context of a European project with relevant French, Belgium and Swiss SMEs that work in the event-based imaging field.

Research grant: The research grant is associated with a yearly renewable contract that includes an experimental period of 6 months. The research grant consists of a tax-free stipend of 1144,64€ per month for PhD position plus tuitions. The candidates must fulfill the following conditions: 

  • Have background on the relevant computer science and electrical and computer engineering areas. Preference will be given to candidates that better understand visual compression, computer vision and image processing fields. 
  • 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 supervise the selected candidate: Prof. João Ascenso and Prof. Catarina Brites (http://amalia.img.lx.it.pt/index.php/team/). The candidate will join a dynamic team of senior members and PhD students where strong research and development activities in the image coding, quality assessment and 3D visual representation fields are carried out. To apply for the research grant, please submit your application by sending an email to joao.ascenso@lx.it.pt with the following documents: 

  1. Detailed curriculum vitae with transcripts (mandatory)
  2. A motivation letter (research statement) explaining your interest in the position (mandatory)
  3. Recommendation letter(s) or a list of individuals with contact information. 

Note that if the above documents are not received, your application may not be considered. Applications shall be received until 31/07/2023. Selected candidates will be submitted to one or more interviews. For any clarifications, please contact Prof. João Ascenso at joao.ascenso@lx.it.pt.

Read more

Postdoc Mathematics and Data Science in Brussels

The research group Digital Mathematics at the Department of Mathematics and Data Science of the Vrije Universitieit Brussel in Belgium is looking for a postdoc in the mathematical foundations for data science (e.g. machine learning, image processing, ...) or post-quantum security. This position requires submitting a project to the Brussels' funding agency Innoviris. More details about the conditions and application procedure at https://we.vub.ac.be/en/dima-digital-mathematics/jobs

Read more