Applies to General Signal Processing

The Department of Mathematics and Data Science of the Vrije Universiteit Brussel is looking for a Tenure Track Professor in Mathematics/Continuous techniques in Data Science with research expertise in mathematical analysis with contributions to data science, more precisely in the combination of knowledge-driven (e.g. using PDE, sparse, geometric or stochastic models) and data-driven approaches for solving inverse problems.

More information on https://jobs.vub.be/job/Elsene-Tenure-Track-Lecturer-MathematicsContinuous-techniques-in-Data-Science/644650201/ 

The Department of Mathematics and Data Science of the Vrije Universiteit Brussel is looking for a Tenure Track Professor in Mathematics/Continuous techniques in Data Science with research expertise in mathematical analysis with contributions to data science, more precisely in the combination of knowledge-driven (e.g. using PDE, sparse, geometric or stochastic models) and data-driven approaches for solving inverse problems.

More information on https://jobs.vub.be/job/Elsene-Tenure-Track-Lecturer-MathematicsContinuous-techniques-in-Data-Science/644650201/ 

Seenel Imaging is hiring its R&D Engineer or equivalent specialized in Signal Processing and C++ Software

Job applies to the following areas: 
Signal Processing Theory and Methods
Computational Imaging
Bio Imaging and Signal Processing
Design and Implementation of Signal Processing Methods
Digital Signal Processing
Image, Video and Multidimensional Signal Processing

www.seenel-imaging.com

Spin off of an INSERM lab located in a University hospital, Seenel Imaging is a start up dedicated to functional Neuro-imaging for Research application. Founded in 2018, Seenel Imaging launched Medelopt®, a wearable research device combining EEG/fNIRS. 

Seenel Imaging is expanding its R&D team to accelerate their product development

Mission

• Implement signal post-processing algorithms in C ++ and OpenCV

• Create proprietary libraries (API, DLLs)

• Create motion artifact correction algorithms for brain imaging

• Develop new software bricks for improving signal quality

• Participate in functional tests of our brain imaging products

• Participate in the correction of software anomalies (bug)

• Participate in the deployment of software projects with our research partners

Background & Expertise

• Ideally 2-3 years of experience in the C++ software applications development 

• Real-time signal processing library (OpenCV)

• Real-time experience

• Curious, creative and rigorous, you do appreciate teamwork and you are above all passionate!

• Engineer or you hold a Master in Signal Processing or equivalent

Having a these additional expertise will be welcome

• Knowledge of the IEC 62304  standard 

• Knowledge of medical devicesEnglish is a Must Have and a 2nd language will be appreciated. Should you have any questions and or interest, would you please contact Seenel Imaging's HR partner.Location: Lille (France)
  
  Permanent Contract 

Please apply for this position here.

Overview:

We invite applications for the position of AI and Embedded Software Senior Researcher to support the ORNL, Radio Frequency (RF) and Intelligent Systems Group in the Electrification and Energy Infrastructures Division (EEID). This position will be a part of a cross-functional team that has responsibility for leading and conducting operational and research activities pertaining to national security and energy systems security. The primary duty of this position is performing R&D to develop software for implementing AI and data processing algorithms on embedded systems for deploying intelligent sensors at the edge. This position will involve working with a team of other researchers and engineers to develop and demonstrate impactful technologies. This position requires an accomplished researcher or engineer with a demonstrated track record in developing AI algorithms and supporting software.

Major Duties/Responsibilities

You will: 

• Design, architect, and prototype software for a variety of embedded AI platforms
• Develop, implement, and test machine learning and signal processing algorithms
• Communicate with customers and end users to establish algorithm and system requirements
• Lead R&D teams to successful outcomes according to project requirements
• Produce technology demonstrations for current and potential sponsors
• Prepare white papers, proposals, and statements of work to attract new or continued funding
• Prepare and deliver presentations to sponsors, technical peers, and at professional society meetings 
• Prepare journal and conference manuscripts for publications
• Prepare technical reports for sponsors, program managers, and technical peers 

Qualifications:

• M.S. or Ph.D. degree in Electrical Engineering, Computer Science, or a related discipline with a minimum of six years of experience (Ph.D.) or 12+ years’ experience (M.S.)
• Experience in developing and applying AI and embedded systems algorithms and software
• Experience with widely used scientific programming languages such as Python, MATLAB, or C++
• Experience in publishing research in scientific journals and conferences
• Experience in technical or scientific writing in order to prepare reports and presentations
• Experience in leading technical teams and developing new projects
• Excellent communication skills

Special Requirements:

This position requires the ability to obtain and maintain a secruity clearance.

ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply.  UT-Battelle is an E-Verify employer.

Autonomous Vehicles at the Intersection of Computer Vision, Machine Learning and Human Factors

About the project

Institute for Transport Studies (ITS) is the leading transportation research centre in the UK and one of the Top 10 global leaders in the field. The centre currently has 60+ research staff and PhD students in multi-disciplinary areas of Human Factors, Computer Vision, AI and Machine Learning, Behavior Modeling, Psychology, and Transportation Safety.

Highly automated vehicles (AVs) also known as Level 4 vehicles can operate in self-driving mode in most circumstances and the driver is allowed to involve in any sort of non-driving activities, even sleeping. However, the automated driving mode is only expected to perform in limited spatial areas (geofenced) and under specific legislations; therefore, a human driver still has the option of getting ready to resume the driving control, whenever required.

This project aims at promoting public trust in automated driving based on scientific investigations and findings on the role of Computer Vision Technology and Human Factors in a smooth technology adaptation and transition. Using machine learning, computer vision, and human factors, the research should investigate whether the driver is ready to safely and swiftly take over the control of the vehicle? What are the major contributing human factors in taking over scenarios and to what extent? Under what circumstances the sensors and autonomous mode can perform safer than a human driver and vice-versa?

The research may involve in-cabin situation awareness such as driver behaviour monitoring (eye, head pose, and body pose modelling), as well as road hazard perception and traffic condition understanding (vehicles, pedestrians and cyclists’ detection & tracking).

While in this research we put more weight in Computer Vision part of the research, the PhD candidate is encouraged to perform joint research within our great interdisciplinary team of psychologists and human factor experts in ITS.

The PhD student is expected to contribute towards one of the following research pathways with a clear and feasible research plan and proposal for a 3.5-year PhD journey.

Possible Research Plans/Directions:

• Development of appropriate methodologies, models, tools, and frameworks to increase automation levels of driving and driver comfort using real-world visual datasets and human factors.
• Using Leeds University Driving Simulator facilities/datasets for eye tracking, driver awareness monitoring, situation awareness monitoring and driver-pedestrian interactions.
• Decision making and risk assessment for switching between human and the automated driving mode, based on real-world visual datasets and sensory information in different driving scenarios.
• Driver behaviour monitoring using visual and psychological measures based on eye and head pose tracking, body pose estimation, and activity recognition.
• In-depth understanding of sensor technologies including Vision, RGB-D, Lidar, Radar, and multi-sensor data fusion research for traffic monitoring and hazard perception.

Entry requirements:

• A Masters Degree in a relevant subject e.g. Computer Science, Engineering, AI, Machine Learning.
• Solid background in applied Computer Vision and Machine Learning
• Demonstrated competency in Math and Statistics
• Demonstrated Programming proficiency (Python and/or C)
• Minimum IELTS Score of 6.5 (no band less than 6.0)

Desired competencies:

• Ability to teamwork in a multidisciplinary research group
• Willingness and plans for joint research in human factors, safety, public trust, and social impact of the research.
• Prior publications in the field

How to Apply:

Enquiries may be addressed to Dr Mahdi Rezaei m.rezaei@leeds.ac.uk

Please provide with your CV, Letter of Motivation, and your PhD proposal (no more than 3 pages).

Further details on application procedures:  https://www.leeds.ac.uk/info/130206/applying/91/applying_for_research_degrees

Country Eligibility:

UK/EU/International

Vertex Postdoctoral Researcher, University of Southern California

Principal Investigator: Urbashi Mitra, Electrical & Computer Engineering and Computer Science

Seeking one to two postdoctoral researchers to work on research problems in a variety of areas:  statistics, learning, structured signal processing, active hypothesis testing, information theoretic measures, interface between machine learning and signal processing and information theory, interface between controls, signal processing and communication etc.  In addition to research, duties include active participation in graduate student mentoring, proposal writing, and project reporting.  High performing postdoctoral researchers are given collaboration opportunities, the chance to interact with funding agency program managers and additional mentoring towards garnering faculty positions.   Past postdoctoral researchers have had PhDs in diverse areas: communications, networking, information theory, statistical signal processing and control – such diversity is welcomed.  Opportunities for inter- and intra-departmental collaboration  also exist. The initial contract is for one year with the possibility of renewal for an additional year (or years) given good performance.  Salary is dependent on candidate experience.  Candidates should be open to making contributions in one of the following application areas:  biological systems (NSF, ARO MURI), underwater actuated sensor networks (ONR, NSF), structured signal processing for physical chemistry (DOE).  All research problems will be jointly designed by the PI and the postdoctoral researcher.  The emphasis is on theoretical research, however,  postdoctoral researchers do work with real data sets and the researchers who generate these data sets.  If there is interest in implementation, projects can be appropriately modified.

Recent postdoctoral researchers from the group have gone onto successful faculty positions at:  UC Irvine, Purdue, IIT Delhi, CUHK Shenzhen, USTC China, Oregon State, etc.

Interested candidates should be nominated by their current advisor (doctoral or postdoctoral) – the advisor should email a cv of the candidate and a brief support statement directly to ubli@usc.edu.  Three letters of recommendation will be requested after the nomination.  Postdoctoral researchers can start immediately.

A postdoctoral scholar position with a focus on applications of machine learning in cardiac MRI. Details can be found at:

https://recruit.ap.uci.edu/JPF05862

The Computational Medicine Laboratory (CML) at the University of Houston is currently looking to recruit one highly motivated and creative Ph.D. student with applied mathematics, signal processing, and/or control theory background to develop mathematical algorithms for biomedical engineering applications with a focus on human subject research.

CML mainly focuses on designing control, optimization, estimation, signal processing, and machine learning algorithms for biomedical and neural engineering applications. The ideal candidate has obtained their B.S. degree in electrical engineering (or related fields, e.g. mechanical, computer or biomedical engineering, computer science, applied mathematics, statistics, etc.) focusing on control theory and/or signal processing.

The projects involve algorithm design and validation in real-time experiments with human recordings. Interested candidates should email Dr. Rose Faghih (email: rtfaghih@uh.edu) with the required documents listed at: http://ComputationalMedicineLab.ece.uh.edu/prospective-students/

Institute of Electronics and Computer Science (EDI) announces the opening of the competition for preliminary selection of postdoctoral applications for submission to the State Education Development Agency (SEDA) under the Activity 1.1.1.2 “Post-doctoral Research Aid” of the Specific Aid Objective 1.1.1 “To increase the research and innovative capacity of scientific institutions of Latvia and the ability to attract external financing, investing in human resources and infrastructure” of the Operational Programme “Growth and Employment”.

The postdoctoral applications must correspond to the main research directions of EDI:

1. Extremely precise event timing for ground and space domains.

2. Signal processing and embedded intelligence.

3. Smart sensors and IoT.

4. Remote sensing and space data processing.

5. Robotics and machine perception.

The deadline for submission is 6 July, 2020.

The postdoctoral researchers intending to participate in the Activity are asked to send (info@edi.lv):

– Curriculum vitae (form by Europass);

– A numbered list of publications;

– The title and the summary of the intended research.

After receiving the required documents, a communication between EDI and the applicant will start on preparing the research application.

More information: +371 67554500; info@edi.lv

Masters students, PhD students and Postdocs interested in the areas of signal processing, machine learning, medical imaging, communications and radar processing. Contact us.