Sensor Array and Multichannel

The Communication Systems Division of the CTTC is searching for interested candidates in a Researcher position for its Advanced Signal and Information Processing (ASIP) Department.

The ASIP Department conducts fundamental and applied research on signal processing and communications, including algorithmic development, theoretical analysis and hardware development. For more information about the department, please refer to http://systems.cttc.es/advanced-signal-and-information-processing/.

TECHNICAL DESCRIPTION OF THE ACTIVITY

The candidate is expected to carry out innovative research on signal processing and machine learning for communications, particularly on the physical and access layers for 6G. The position offers excellent opportunities to develop both fundamental and applied research on wireless communication networks, bringing your personal impact to the Division’s significant contributions. As member of the ASIP department the selected candidate will

• Participate in the preparation of R&D competitive and industrial project proposals
• Lead and participate in the execution of R&D projects
• Contribute to the definition and development of the Division and ASIP department research activities
• Support the department on demonstrations and experimental activities

The position also involves the establishment of cooperation and collaboration with external entities, as well as encourages visibility and impact through the organization and participation at international conferences, congresses, standardization bodies or industrial associations.

QUALIFICATIONS AND EXPERIENCE

Applicants must hold a Ph.D. degree in telecommunications, computer science, electrical engineering, or closely related fields. We are looking for a highly motivated candidate capable of conducting independent research, as well as demonstrating excellent skills to carry out highly innovative R&D work in collaborative projects and industrial projects. Required skills and experience:

• Strong background in the following specialization areas of interest: Signal Processing for Communications, Machine Learning
• Capacity to pursue independent research and very good analytical and problem-solving skills,
• Excellent track publication record and capacity of attracting competitive funds,
• English written proficiency and good communication skills,
• R&D work experience in physical and access layers for wireless communications
• Preparation of research grant proposals such as EC funded programs,
• Very good programming skills in Matlab and Python.
• Management and participation in international and national R&D projects

Other valuable skills:

• Good programming skills in C and C++.
• Experience in experimental developments (Software Defined Radio, GNU Radio, etc)
• Proven experience in coordination/task leadership in European and other international research projects.

CONDITIONS

The position is temporary, investigador/a interino/a, according to the Spanish national law. An interim contract for vacancy is issued to temporarily cover a permanent position during the selection or promotion process for its definitive coverage, expected to take place within 3 years of the approval of the public offer of occupation with regards to the vacant permanent position. The position lies within the R2-R3 professional category at CTTC. The rank and salary will be determined according to qualifications and work experience. The salary will be in the range between 37.600 and 41.500 euro (gross per year).

We offer high standards working conditions, under a flexible and international environment with access to cutting-edge experimental facilities and excellent professional and personal development possibilities.

The application shall include a full curriculum vitae, including list of publications, a cover letter stating the motivation and suitability of the candidate. They should also provide the names and contact details (email address, etc.) of at least two referees.

These documents should be sent in PDF format through this online application. CVs and any other information gathered during this process will be handled confidentially.

The deadline for applications is January 17th, 2021.

CTTC

Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), in Castelldefels – Barcelona, is a growing and well-funded research institution fostering excellence and diversity. CTTC offers a highly international environment at an exceptionally attractive location.

As a research center in telecommunications technologies CTTC provides a fertile environment for research cooperation and innovation between different disciplines. CTTC seeks to increase the number of women in those areas where they are underrepresented and therefore explicitly encourages women to apply. CTTC is committed to increasing the number of individuals with disabilities in its workforce and therefore encourages applications from such qualified individuals.

Apply now: http://www.cttc.es/apply/?id=12862

A full time one-year position as a postdoctoral Fellow is available at the AViReS Lab ( https://avires.dimi.uniud.it ) of the Department of Mathematics, Computer Science and Physics (DMIF), University of Udine.   

The postdoc fellow will work with an interdisciplinary team of experienced researchers in the fields of audio signal processing, computer vision, machine learning, robotics. Primary co-mentors will be Prof. Carlo Drioli and Prof. Gian Luca Foresti. The goals of his research will be to develop specific methods and algorithms allowing to improve the effectiveness of localization and tracking of a moving target through the dynamic reconfiguration of a sensor network, to study the integration possibilities of acoustic and optical sensors with respect to the problem under study, to address application scenarios related to the use of mobile robotic platforms, in particular autonomous aerial drones (UAVs/MAVs) equipped with acoustic and optical sensors.
The research activities will be normally conducted at the AViReS Lab facilities in Udine. However note that, due to the ongoing Covid-19 outbreak, it is possible that for the first few months the activities will have to be conducted remotely.  
Total grant payd by the financer amounts to 19.367,00 Euros.

Application deadline is May 12, 2020 at 02:00 p.m. (Italian time).

Please contact Carlo Drioli (carlo.drioli@uniud.it) or Gian Luca Foresti (gianluca.foresti@uniud.it) for any further questions.

Detailed information and directions to apply can be found at the following links: 

http://web.uniud.it/ateneo/normativa/albo_ufficiale/258-2020/DRN_188_2020_Notice%20of%20competition_.pdf
http://web.uniud.it/ateneo/normativa/albo_ufficiale/258-2020

A one-year position as a postdoctoral fellow is available at the AVIRES Lab ( https://avires.dimi.uniud.it ) of the Department of Mathematics, Computer Science and Physics (DMIF), University of Udine.   

The postdoc fellow will work with an interdisciplinary team of experienced researchers in the fields of audio signal processing, computer vision, machine learning, robotics. The goals of his research will be to develop specific methods and algorithms allowing to improve the effectiveness of localization and tracking of a moving target through the dynamic reconfiguration of a sensor network, to study the integration possibilities of acoustic and optical sensors with respect to the problem under study, to address application scenarios related to the use of mobile robotic platforms, in particular aerial drones equipped with acoustic and optical sensors. 

Details here.

Application deadline is March 17, 2020 at 02:00 p.m. (Italian time).

Please refer to the links below or contact Carlo Drioli (carlo.drioli@uniud.it) for further questions.

Detailed information and directions to apply can be found at the following link: http://web.uniud.it/ateneo/normativa/albo_ufficiale/146-2020 

The aim of this postdoc project is to develop a novel ultrasound methodology that enables non-invasive read-out of the acoustic properties of radiation-sensitive microbubbles in order to construct a dose map. Hereto, acoustic models of wave propagation through soft tissue will be combined with advanced signal processing techniques. The developed methodology will extensively be validated in experimental setups (both in-vitro and in-vivo).

Profile:

• You have a PhD degree in (wave) physics, signal processing or biomedical engineering
• You have a solid mathematical background enabling to understand physical models
• You have a strong interest in wave physics and signal processing
• You are practical and can build experimental setups independently
• Being familiar with ultrasound imaging and its applications is an asset
• You have good programming skills in Matlab and/or in C/C++
• You are fluent in oral and written English
• You are enthusiastic and result oriented
• You can work independently with a critical mind set
• You have strong team-player skills
• You have NOT worked in Belgium in the past 3 years (this is a funding requirement)

Offer: We offer a postdoc position for 2 years with a market conform wage in a large, multidisciplinary research center in the heart of Europe, at a highly-ranked university. The position is immediately available and is co-supervised by experts in the field of ultrasound imaging and signal processing.

Interested?

Immediate opening for a postdoctoral researcher in radionavigation and wireless communication systems at the Autonomous Systems Perception, Intelligence, & Navigation Laboratory (https://aspin.ucr.edu); University of California, Irvine (https://uci.edu).

Desired qualifications: (1) Ph.D. in Electrical and Computer Engineering, Aerospace Engineering, or a closely related field; (2) knowledge of wireless communications and/or GNSS; (3) demonstrated hands-on expertise in software-defined radio (SDR) design and implementation; (4) strong programming skills (MATLAB, LabVIEW, and/or C++); (5) publications in relevant top-tier journals and conference proceedings; (6) strong communication, presentation, and documentation skills; and (7) ambition to become a leader in the field (e.g., Professor, Senior R&D Engineer, Managing Technical Director, Program Manager, etc.). To apply, please email me: (1) a complete CV, (2) up-to-date university transcripts, (3) a short statement describing research interests and goals, (4) names and contacts of 3 references, and (5) a link to your website (if available). Position duration: minimum of 1 year, extendable up to 3 years.

Online Applications only: http://emea3.mrted.ly/28n6x

The University of Luxembourg is a multilingual, international research university.

The Interdisciplinary Centre for Security, Reliability and Trust (SnT) invites applications from PhD candidates in the general area of signal processing for extremely high frequency sensing and communication applications. SnT carries out interdisciplinary research in secure, reliable and trustworthy ICT systems and services, often in collaboration with industrial, governmental or international partners.

Your Role

Position Description:

Radar sensor based driver assistance systems for automotive applications are currently under investigation to increase comfort and safety of drivers.  Presence of radar functionality on multiple cars leads to a network of radar sensors which can be exploited to enhance the environment sensing. An emergent automotive scenario is collaborative sensing, where the cars sense and communicate about the emergency situations (like obstacles, braking, accident etc.). The dynamics of the scenario, e.g., number and position of the cars, preclude a central processing unit there by motivating the network radar. Recent advances in wireless communication technology can be exploited to realize a network radar. Further, due to spectrum allocation trends and requirements of high bandwidth, an investigation of extremely high frequencies, namely mmWave and beyond bands (with a corresponding wavelength of about 1 mm), has been attracting significant attention in both the automotive radar industry as well as the mobile community. Compared to microwaves, operation in higher bands provides access to larger bandwidth enabling higher range resolution and fine details of the targets as well as higher data rates. Besides, the size of system components such as the antennas required to process the such signals reduces drastically; this enables the possibility of accommodating high number of antenna elements on the device to enhance the spatial resolution. Further, their incorporation on a moving platform, e.g., automobile, results in a synthetic aperture radar (SAR) / inverse synthetic aperture radar (ISAR) whose advantages are well documented. However, to explore and exploit the advantages of such network radar systems, several research challenges need to be solved. The research will focus on devising optimization algorithms to enhance the performance of MIMO radar networks in waveform optimization, target detection, classification and localization while leveraging advances in wireless communications.

The position holder will be required to perform the following tasks:

• Carrying out research in the field of signal processing algorithms for MIMO radar networks in extremely high frequencies co-existing with communications
• Disseminating results through scientific publications

For further information, please contact us at Mohammad.Alaee@uni.lu or Bhavani.Shankar@uni.lu

Your Profile

Qualification: The candidate should possess an MSc degree or equivalent in Electrical/Electronic Engineering, Computer Science or Applied Mathematics. The successful candidates will join a strong and motivated research team lead by Prof. Björn Ottersten and Dr. Bhavani Shankar in order to carry out PhD.

Experience: The ideal candidate should have some knowledge and experience in a number of the following topics:

• Signal processing techniques for distributed sensors
• Developing scientific algorithms in the fields of mmWave (and beyond) radar signal/image processing
• Waveform design and optimization algorithms applied to the radar systems
• Machine/Deep Learning with applications to radar systems including Automatic target classification and recognition algorithms (including CNN and DNN)

and have a  strong background in

• Optimization theory
• Linear algebra and statistics
• Statistical Signal processing

Development skills in MATLAB, is required. Exposure to USRP/SDR implementation and familiarity with LabView, C++, and FPGA programming is considered as an advantage.

Language Skills: Fluent written and verbal communication skills in English are required.

We offer

The University offers a Ph.D. study program with a Fixed Term Contract up to 3 years in total, pending satisfaction of progress milestones (CDD), full-time (40 hrs/week). The University is an equal opportunity employer. The candidate will work in an exciting international environment.

Further Information

Application should be sent online, in English and should include:

• Full CV, including list of publications and names (and contact information including email addresses) of three references
• Transcript of all modules and results from university-level courses taken
• Research statement and topics of particular interest to the candidate (300 words).

All qualified individuals are encouraged to apply. The University of Luxembourg is an equal opportunity employer. The last date for application is September 15, 2019. Applications will processed as they arrive; early application is highly encouraged. Please apply online here:  http://emea3.mrted.ly/28n6x

Online Application Only:http://emea3.mrted.ly/28f97

The University of Luxembourg is a multilingual, international research university.

The Interdisciplinary Centre for Security, Reliability and Trust (SnT) invites applications from PhD holders for conducting research in design and optimization methods for performance enhancement of next generation radar networks

SnT is carrying out interdisciplinary research in secure, reliable and trustworthy ICT systems and services, often in collaboration with industrial, governmental or international partners. The SIGCOM group in SnT is pursuing research on automotive radar applications in partnership with IEE (www.iee.lu), a Luxembourg based global leader in automotive safety sensing systems for occupant detection and classification. Recently, Prof. Bjorn Ottersten Director of SnT and head of SIGCOM, has been awarded the prestigious European Research Council (ERC) Advanced Grant to pursue research on cognitive radar systems with applications to automotive radar. For further information, you may visit www.securityandtrust.lu and http://wwwen.uni.lu/snt/research/sigcom.

Project Description

As novel applications emerge, the requirements on radar systems have grown significantly from being “a blip on the radar”, to providing an image like reconstruction of the surroundings. Currently, multi-static and widely-separated MIMO radars offer multi-view perspective. However, these systems suffer from the need for high rate synchronization, lack of performance guarantees, minimal exploitation of advances in waveform processing and machine learning among others. Thus, it is essential to go beyond the mature co-located MIMO and the current widely-separated MIMO radars towards achieving reliable imaging like performance for extended targets. In fact, many of these networks, such as in the automotive scenario, can involve large number of dynamic nodes. This necessitates devising novel radar-network architectures as well as exploring various optimization methodologies for waveform design, super-resolution parameter estimation and decentralized resource allocation.  

This emerging field opens interesting avenues for pursuing research in radar signal processing, especially on

• Relevant architectures for novel radar networks including information exchange mechanisms for identified use cases
• Associated signal processing elements including development of optimization algorithms for waveform, receiver design including high-resolution parameter estimation as well as their adaptation to dynamic scenarios
• System optimization using model based mechanisms as well as machine learning approaches; deep unfolding applications

The research associates will have further the opportunity to work towards in-lab demonstration of the developed techniques using USRP/SDR implementations.

The SIGCOM research group is in a unique position towards realizing the objectives of the project having exposure to radar signal processing through ongoing research projects, evolution of communication standards through participation and contribution as well as experience with prototype chip sets from the test-bench development activity.

Your Role

The successful candidates will join a strong and motivated research team lead by Prof. Björn Ottersten in order to carry out research in the area of signal processing for next generation radar systems.

The position holder will be required to perform the following tasks:

• Shaping research directions in line with project objectives, pursuing research and delivering project outputs
  • Carrying out cutting edge research activities in architectural definition, waveform design and receiver processing, enabling cognition in next generation radar networks
  • Participating in development and upgradation of the SDR based Radar test bench based on pursued research is considered as a plus
• Disseminating the results through scientific publications in high impact factor journals
• Presenting the results in the internationally well-known conferences and workshops
• Attracting funding in cooperation with partners
• Providing guidance to PhD and MSc students
• Assisting in teaching duties
• Organizing relevant workshops

For further information, please contact Bhavani.Shankar@uni.lu or Bjorn.Ottersten@uni.lu

Your Profile

Qualification: The candidate should possess (or be in the process of completing) a PhD degree or equivalent in Electrical/Electronics Engineering, Computer Science or Applied Mathematics.

Experience: The ideal candidate should have research project-based experience (FP7/H2020, Industry) and publication record in a number of the following topics:

• Optimization methodologies with application to Radar Systems
• Machine/Deep Learning with applications to Radar Systems
• Widely-separated MIMO Radar System, Waveform Design and Receiver processing
• Statistical Signal Processing

Exposure to USRP/SDR implementation and familiarity with FPGA programming is considered as an advantage. Development skills in one of the programming languages, MATLAB, LabVIEW or C++ are required.

Exposure to the latest radar technology and digital communications is desirable.

Language Skills: Fluent written and verbal communication skills in English are required.

We offer

The University offers a two-year employment contract that may be extended up to five years. The University is an equal opportunity employer. You will work in an exciting international environment and will have the opportunity to participate in the development of a newly created university.

Further Information

Application should be submitted online and include:

• Full CV, including list of publications and name (and email address, etc.) of three referees
• Transcript of all modules and results from university-level courses taken
• Research statement and topics of particular interest to the candidate (300 words)

Deadline for applications:  September 15, 2019.  Applications will be processed as they arrive; early application is highly encouraged.

Online Applications Only:  http://emea3.mrted.ly/28n6x

The University of Luxembourg is a multilingual, international research university.

The Interdisciplinary Centre for Security, Reliability and Trust (SnT) invites applications from PhD candidates in the general area of signal processing for extremely high frequency sensing and communication applications. SnT carries out interdisciplinary research in secure, reliable and trustworthy ICT systems and services, often in collaboration with industrial, governmental or international partners.

We are currently pursuing research on automotive radar applications in partnership with IEE (www.iee.lu), a Luxembourg based global leader in automotive safety sensing systems. Recently, Prof. Bjorn Ottersten Director of SnT, has been awarded the prestigious European Research Council (ERC) Advanced Grant to pursue research on cognitive radar systems with applications to automotive radar, this activity is now expanding to develop next generation signal processing techniques for MIMO radar. For further information, kindly refer to: www.securityandtrust.lu and http://wwwen.uni.lu/snt/research/sigcom.

Your Role

Radar sensor based driver assistance systems for automotive applications are currently under investigation to increase comfort and safety of drivers.  Presence of radar functionality on multiple cars leads to a network of radar sensors which can be exploited to enhance the environment sensing. An emergent automotive scenario is collaborative sensing, where the cars sense and communicate about the emergency situations (like obstacles, braking, accident etc.). The dynamics of the scenario, e.g., number and position of the cars, preclude a central processing unit there by motivating the network radar. Recent advances in wireless communication technology can be exploited to realize a network radar. Further, due to spectrum allocation trends and requirements of high bandwidth, an investigation of extremely high frequencies, namely mmWave and beyond bands (with a corresponding wavelength of about 1 mm), has been attracting significant attention in both the automotive radar industry as well as the mobile community. Compared to microwaves, operation in higher bands provides access to larger bandwidth enabling higher range resolution and fine details of the targets as well as higher data rates. Besides, the size of system components such as the antennas required to process the such signals reduces drastically; this enables the possibility of accommodating high number of antenna elements on the device to enhance the spatial resolution. Further, their incorporation on a moving platform, e.g., automobile, results in a synthetic aperture radar (SAR) / inverse synthetic aperture radar (ISAR) whose advantages are well documented. However, to explore and exploit the advantages of such network radar systems, several research challenges need to be solved. The research will focus on devising optimization algorithms to enhance the performance of MIMO radar networks in waveform optimization, target detection, classification and localization while leveraging advances in wireless communications.

The position holder will be required to perform the following tasks:

• Carrying out research in the field of signal processing algorithms for MIMO radar networks in extremely high frequencies co-existing with communications
• Disseminating results through scientific publications

For further information, please contact us at Mohammad.Alaee@uni.lu or Bhavani.Shankar@uni.lu

Your Profile

Qualification: The candidate should possess an MSc degree or equivalent in Electrical/Electronic Engineering, Computer Science or Applied Mathematics. The successful candidates will join a strong and motivated research team lead by Prof. Björn Ottersten and Dr. Bhavani Shankar in order to carry out PhD.

Experience: The ideal candidate should have some knowledge and experience in a number of the following topics:

• Signal processing techniques for distributed sensors
• Developing scientific algorithms in the fields of mmWave (and beyond) radar signal/image processing
• Waveform design and optimization algorithms applied to the radar systems
• Machine/Deep Learning with applications to radar systems including Automatic target classification and recognition algorithms (including CNN and DNN)

and have a  strong background in

• Optimization theory
• Linear algebra and statistics
• Statistical Signal processing

Development skills in MATLAB, is required. Exposure to USRP/SDR implementation and familiarity with LabView, C++, and FPGA programming is considered as an advantage.

Language Skills: Fluent written and verbal communication skills in English are required.

We offer

The University offers a Ph.D. study program with a Fixed Term Contract up to 3 years in total, pending satisfaction of progress milestones (CDD), full-time (40 hrs/week). The University is an equal opportunity employer. The candidate will work in an exciting international environment.

Further Information

Application should be sent online, in English and should include:

• Full CV, including list of publications and names (and contact information including email addresses) of three references
• Transcript of all modules and results from university-level courses taken
• Research statement and topics of particular interest to the candidate (300 words).

All qualified individuals are encouraged to apply. The University of Luxembourg is an equal opportunity employer. The last date for application is September 15, 2019. Applications will processed as they arrive; early application is highly encouraged..Please Apply Online http://emea3.mrted.ly/28n6x

The ELIOT project aims to study communication networks of interconnected devices that lie at the core of many key future technologies such as distributed control systems for autonomous vehicles, sensor networks for structural health monitoring and for smart cities. In addition to reliability, all these applications come with strict requirements in terms of: energy efficiency, security, latency and self-optimization capabilities, and demand for innovative enabling technologies. The 
emerging Internet of Things (IoT) paradigm, projected to connect billions of wireless "things" (wireless sensors, wearables, biochip transponders, etc.) in a vast network with drastically different characteristics among its components, has moved from being a futuristic vision to an increasing reality over the recent years.

This Post-Doctoral position involves the study of physical-layer algorithms such as transmit and receive beamforming, and coding schemes algorithms used in IoT networks taking into account the need for low power consumption and different requirements in latency and rate, and their use in conjunction with coarse quantization schemes.  In particular, the work involves the application to large-scale systems where robust transmit beamforming or precoders can be designed based on work done for robust beamforming with sensor arrays, robust techniques and resource allocation.

While joint coding/beamforming techniques have been available already for some time, the goal of this research is to develop novel robust beamforming methods that take into account the requirements of IoT networks equipped with multiple antennas and the use of coarse quantization.

Candidates should have a strong background on signal processing and telecommunications, particularly array processing and coding.  The scholarship includes funding for relocation to Sao Paulo.

This is a joint research project between the USP, (Brazil), PUC-Rio (Brazil) and ENSEA (France).  The researcher will be based at USP in Sao Paulo, but may spend periods also in PUC-Rio and ENSEA.

Apply here: https://www.kuleuven.be/personeel/jobsite/jobs/55004357?hl=en&lang=en

Project: 

This job opening covers a research position at the STADIUS group of the Department of Electrical Engineering (ESAT) of KU Leuven (Belgium) for a Ph.D. candidate in the frame of an ERC project on signal processing algorithm design for next-generation wearable neuro-technology and neuro-sensornetworks.  A specific focus is on the design of adaptive multi-channel neural signal processing algorithms, amenable to low-power distributed or parallellizable architectures with constrained energy resources.

Profile

Candidates must hold a Masters degree in Electrical or Computer Science Engineering (or equivalent) with excellent grades, and with a strong mathematically-oriented engineering background. A good knowledge in the following fields is deemed necessary:

-Signals and systems

-Linear algebra

-Signal processing 

-Analysis of random/stochastic signals (stationarity, power spectral density, estimation theory, Wiener, etc.) 

Additional research/educational experience in any of the following topics is a plus:

- Multi-channel signal processing and spatial filtering

- (Blind) source separation

- Sensor array processing (beamforming, detection, …)

- (Convex) optimization theory 

- Brain-computer interfaces and neural decoding

- Component analysis theory and application (PCA, ICA, IVA, CCA, …)

- Machine learning (deep or not)

Candidates should be motivated, independent, critical, and should have strong team-player skills. Excellent proficiency in the English language is also required, as well as good communication skills, both oral and written.

Offer