Computational Imaging

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

Applying tomographic SAR inversion using compressive sensing is well established in the SAR community. In contrast to state of the art approaches applied to satellite data novel CS reconstruction approaches combining sparsity with prior information will be researched and implemented. We intend to use high resolution airborne data sets from FHR and later, from our own sensor platform. The data is superior to satellite data concerning resolution und SNR. The main goal is the evaluation of the used CS methods for remote sensing 3-D imaging. Additionally, the performance in layover areas and the super-resolution properties will be checked. The developed methods will be compared with the state of the art.

The successful candidate will be employed for a maximum period of three years full-time equivalent and receives a generous financial package plus an additional mobility and family allowance according to the rules for Early Stage Researchers (ESRs) in an EU Marie Sklodowska-Curie Actions Innovative Training Networks (ITN). A career development plan will be prepared for each fellow in accordance with his/her supervisor and will include training, planned secondments and outreach activities in partner institutions of the network. The ESR fellows are supposed to complete their PhD thesis by the end of the 3rd year of their employment. For more information please visit the Marie Sklodowska-Curie Actions Innovative Training Networks website.

YOUR TASKS

• Simulation and evaluation of the theoretical limits regarding coherence and resolution using CS in tomographic SAR for the used configurations
• Design of the signal and noise model of the tomographic geometry for sparse reconstruction.
• Development of novel CS reconstruction algorithms incorporating prior information.
• Working with real data including high resolution SAR processing and 3D scene reconstruction.
• Planning and realization of tomographic experiments using the SAR sensor of ZESS.
• identify advantages and limitations by synthetic and experimental tests.

PROFILE

• Master of Science in Electrical Engineering, Electronics Technology, Electrical Engineering Technology, Electrical and Computer Engineering, Physics, Industrial Engineering, Information Technologies or related fields
• ESRs must demonstrate that their ability to understand and express themselves in both written and spoken English is sufficiently high for them to derive the full benefit from the network training. Non-native English speakers are required to provide evidence of English language competency. (TOEFL … )
• Some basic knowledge on signal processing and radar technology

PLANNED SECONDMENTS

• FHG (FHR), Wachtberg, Germany, Dr. P. Berens, 5 months, working with real airborne TomoSAR data.
• WIS (SAMPL) , Israel, Prof. Dr. Yonina Eldar, 2 months, work on CS reconstruction algorithms and compare with own approaches.
• GAMMA, Bern, Switzerland, Dr. U. Wegmüller, 2 months, CS algorithm refinement, optimization, and analysis.

ADDITIONAL INFORMATION

Contact and further Information

https://www.uni-siegen.de/zess

A question that naturally arises in active sensing systems, such as ToF systems, is how much volume can be sensed with a given power budget, and how this can be extended by means of some more intricate sensing scheme. The main objective of this project is the development of a very-wide-area ToF 3D sensing system which has to be outstandingly efficient regarding the power consumption. To attain such an ambitious goal we propose bringing compressive sensing into the game and using recently proposed adaptive methods for constructing close-to-optimal binary sensing matrices. Such matrices, initially developed at ZESS for use in pulsed ToF, are able to progressively concentrate the sensing power in those regions of the domain where the signals (e.g., sparse targets) live. This way the SNR of the measurements can be effectively improved by synthetically reducing the signal domain or, complementary, increasing the range of the system without increasing the power budget.

The successful candidate will be employed for a maximum period of three years full-time equivalent and receives a generous financial package plus an additional mobility and family allowance according to the rules for Early Stage Researchers (ESRs) in an EU Marie Sklodowska-Curie Actions Innovative Training Networks (ITN). A career development plan will be prepared for each fellow in accordance with his/her supervisor and will include training, planned secondments and outreach activities in partner institutions of the network. The ESR fellows are supposed to complete their PhD thesis by the end of the 3rd year of their employment. For more information please visit the Marie Sklodowska-Curie Actions Innovative Training Networks website.

YOUR TASKS

• Evaluation of the possibilities and main trade-offs of a very-wide-area ToF 3D sensing system.
• The advantages of implementing close-to-optimal binary sensing matrices for acquiring the measurements are to be evaluated. The performance improvement attained by means of adaptive construction methods is to be evaluated. Adaptation is first to be considered in depth domain and then extended to the full 3D space.
• Building upon the previous results, the ESR should select or develop his own tailored sensing strategies.
• For the selected sensing schemes, realistic requirements for the hardware to develop should be defined.
• A final hardware design is to be outlined and constructed, according to the selected sensing scheme and system requirements. The system has to be composed by a high power modular illumination system and a ToF camera able to use custom binary codes as control signals. The latter can be a solution provided either by CiTIUS or pmdtec. The performance of the prototype as 3D imaging system is to be evaluated, both in controlled scenes and real-world scenes, and contrasted to the initial simulation results. Different methods for reconstructing the (sparse) 3D scene are to be considered that exploit the structure in the sensing matrix and side information from adaptation.
• The performance of the prototype as 3D imaging system is to be evaluated, both in controlled scenes and real-world scenes, and contrasted to the initial simulation results. Different methods for reconstructing the (sparse) 3D scene are to be considered that exploit the structure in the sensing matrix and side information from adaptation.

PROFILE

• Master of Science in Electrical Engineering, Electronics Technology, Electrical Engineering Technology, Electrical and Computer Engineering, Physics, Industrial Engineering, Information Technologies or related fields
• Master of Science in Electrical Engineering, Electronics Technology, Electrical Engineering Technology, Electrical and Computer Engineering, Physics, Industrial Engineering, Information Technologies or related fields
• ESRs must demonstrate that their ability to understand and express themselves in both written and spoken English is sufficiently high for them to derive the full benefit from the network training. Non-native English speakers are required to provide evidence of English language competency (TOEFL, …).
• Knowledge and experience on scientific programming languages, e.g., Matlab, Python, C, C++, etc.
• Some basic knowledge on signal processing and Time-of-Flight imaging
• Knowledge on compressive sensing would be an advantage

PLANNED SECONDMENTS

• INSITU, Vigo, Spain, Prof. Dr. P. Arias Sánchez, 4 months, real-world performance evaluation of the prototype. Prospective applications. Testing in INSITU mobile platforms.

ADDITIONAL INFORMATION

Contact and further Information

https://www.uni-siegen.de/zess

Algorithms for Event-Driven Camera Analysis

School of Computing, Engineering and Mathematics

Scholarship code: 2019-089

https://www.westernsydney.edu.au/graduate_research_school/graduate_research_school/scholarships/current_scholarships/current_scholarships/scem_algorithms_for_event-driven_camera_analysis

About the project

Event-driven cameras are exciting technology that do not acquire full images like traditional cameras, but record only intensity changes when they occur. The International Centre for Neuromorphic Systems at Western Sydney University has been adapting them to perform Neuromorphic space imaging.

This PhD scholarship builds on this work to help develop the correct abstraction and a theory so as to improve knowledge extraction algorithms. It goes from modelling to algorithm testing using real data, working together with a world-class team.

What does the scholarship provide?

• Domestic candidates will receive a tax-free stipend of $30,000(AUD) per annum for up to 3 years to support living costs, supported by the Research Training Program (RTP) Fee Offset.
• International candidates will receive a tax-free stipend of $30,000(AUD) per annum for up to 3 years to support living costs. Those with a strong track record will be eligible for a tuition fee waiver.
• Support for conference attendance, fieldwork and additional costs as approved by the School.

International candidates are required to hold an Overseas Student Health Care (OSHC)(opens in new window)insurance policy for the duration their study in Australia. This cost is not covered by the scholarship.

Eligibility criteria

The successful applicant should:

• hold qualifications and experience equal to a Masters in the fields of Data Science, Computer Science, Applied Mathematics, Electrical Engineering or similar fields.
• have programming experience (ideally Python)
• be knowledgeable in topics such as signal processing, algorithms, probability and statistics.
• have the ability to think abstractly and deeply.
• have the ability to work in a team of highly motivated engineers, computer and data scientists, and applied mathematicians.
• be highly motivated to tackle challenging problems, with a desire to learn and grow.

The Institution for Future is a newly established department in Qingdao University, nestling under the mountain and beside the sea in the beautiful coastal city of Qingdao. We have millions of funding and now seeking for some teammates who wish to lead the future with us. The following five labs are opening for candidates at all ranks (Post-Docs, assistant, associate, and full professor):

• Lab of Artificial Intelligence
• Lab of Robotics
• Lab of Intelligent Manufacture
• Lab of Unmanned Systems
• Lab of Fundamental Research

We are interested in candidates in broad areas, including but not limited to: control theory and technology, computer science, signal processing, robotics, unmanned systems, artificial intelligence. You will be given large freedom for your own research and/or industrial projects.

The assistant professor position and Post-Doc position is only for young scientists under 35. The Post-Doc position lasts about 2 years (usually no less than 20 months, no more than 3 years). Special offers are available for outstanding candidates now.

To apply or to request more information, please contact jwy1992@126.com as soon as possible. Application documents should include a detailed CV, publication record, your best 2 papers, and preferably a proposal for your future research.

Postdoctoral Researcher/Doctoral Student/Project Researcher (Imaging/Sensing/Automatic control), 1-3 positions

The Signal and Image Restoration Group is part of the Laboratory of Signal Processing at Tampere University of Technology. The group research is dedicated to the characterization, transformation, and filtering of noise and other degradations for a variety of consumer, medical, and scientific imaging devices. The group develops theoretically grounded models, methods, and regularization priors for unsupervised processing of data from a diverse range of sensors, including direct, inverse, as well as computational imaging systems, with the ultimate goal of substantially improving the sensing/imaging quality and extending the applicability and efficiency of these devices. It has a strong scientific profile and is involved in national and international projects with both academic and industrial partners.

Job description:    

The Signal and Image Restoration Group is currently looking for motivated and talented postdoctoral and doctoral-student level researchers to contribute to ongoing research projects. The main problems to be investigated include image sensing and restoration at extremely low energy levels (with application to inverse problems in physics and medicine), and adaptive control of ultrafast broadband laser sources.

The positions are strongly research focused. Activities include conducting empirical research, theoretical analysis, algorithm design, software development and validation, reading and writing scientific articles, presentation of the research results at seminars and conferences in Finland and abroad, acquiring (or assisting in acquiring) further funding.

Candidates hired for Doctoral Student positions will work towards completion of a PhD degree under the supervision of the senior members of the research group.

Requirements:    

Candidates should hold a master or doctoral degree in image processing, computer science and/or engineering, data science, applied mathematics, or related areas.

Candidates are also expected to have good skills in scientific programming (preferably Matlab, Python, and/or C), proficiency in English, both written and spoken.

The following qualities are appreciated:

 * a strong background in linear algebra, statistical estimation, machine learning, and/or numerical optimization;

 * experience working with real data;

 * experience working with sensors and control systems.

Candidates at the postdoctoral level must have a demonstrated ability to carry out independent research in at least one of the following fields: signal and image processing, machines learning, multivariate statistics.

Information and application instructions:
https://careers.fi/tty/careers.cgi?action=view&job_id=1353&lang=uk

Lightfields Rendering and Representation.  The EmergIMG project results from a Portuguese consortium that targets to design a common framework for the representation and quality assessment of emerging imaging modalities, including lightfields and holographic imaging. This consortium aims to boost an international impact in terms of research and standardization. This research grant is included in this project and it is intended the analysis of lightfields data, namely the study and development of new representation and rendering models, quality evaluation models and the possible common representation with holographic data.