Vous êtes ici : Accueil » Kiosque » Annonce

Identification

Identifiant: 
Mot de passe : 

Mot de passe oublié ?
Détails d'identification oubliés ?

Annonce

14 juillet 2020

Edinburgh, GB : Research Associate in Computational Imaging Methods for Quantum Enhanced Imaging


Catégorie : Post-doctorant


https://www.hw.ac.uk/uk/jobs/job_SVJDMjc0NDM.htm

 

https://www.hw.ac.uk/uk/jobs/job_SVJDMjc0NDM.htm

 

Vacancy title
Research Associate in Computational Imaging Methods for Quantum Enhanced Imaging
Job ref
IRC27443
Closing date
20 Jul 2020 23:00 (UK time)
Salary
£32,817– £40,322 (Grade 7)
Location
Edinburgh
Department
The Institute of Signals, Sensors and Systems
Category
Academic and Research
Status
Full-time
Duration
24 months fixed-term

 

Position Title Research Associate in Computational Imaging Methods for Quantum Enhanced Imaging
     
Location Edinburgh, GB
     
Organization Name The Institute of Signals, Sensors and Systems
     
About Heriot-Watt University
     
   

Heriot-Watt University has five campuses: three in the UK (Edinburgh, Scottish Borders and Orkney), one in Dubai and one in Malaysia. The University offers a highly distinctive range of degree programmes in the specialist areas of science, engineering, design, business and languages.

With a history dating back to 1821, Heriot-Watt University has established a reputation for world-class teaching and practical, leading-edge research, which has made it one of the top UK universities for business and industry. We connect with industry at every level and develop programmes to match their needs – so employers get work-ready industry-fit graduates.

Heriot-Watt is also Scotland's most international university, boasting the largest international student cohort.

We have an established set of values that help us to nurture innovation and leadership, and show our commitment to continuous improvement and development in all our activities.

For full details on our University please view our Careers at Heriot-Watt http://www.hw.ac.uk/about/careers-at-heriot-watt.htm

     
About our Team
     
   

The Institute of Signals, Sensors and Systems (ISSS) is one of five Research Institutes forming the research infrastructure of the School of Engineering & Physical Sciences (EPS). With 30 academic members of staff spanning 10 nationalities and 4 fields of expertise, ISSS aims to offer the full portfolio of expertise in the fields of signal and image processing, novel manufacturing technologies, microsystems, microwave engineering, mobile communications systems and autonomous systems. Of particular interest to ISSS is the design, modelling, simulation, processing of information from and system integration of sensors. The Signal and Image Processing Laboratory (SIPLab) at Heriot-Watt specializes in the design of advanced data science techniques with applications ranging from robotics to imaging and communication, in a large variety of fields including defence, astronomy, art investigation, or medicine. Our research activities range from signal and image processing theory to application, and impact different areas of society. SIPLab is active in both traditional and emerging areas, and currently covers the following topics:

Signal and image processing theory

Statistical signal/image processing, Bayesian inference, statistical and physical modelling, optimization algorithms, stochastic approaches, Monte Carlo simulation methods, decision theory, uncertainty quantification, machine learning, hybrid algorithms, sensing methods, theoretical performance, parallel computing strategies.

Applications and areas of key innovation

Computational imaging, high-dimensional data, multi-sensor data fusion, extreme/real world scenarios, low illumination sensing, fast 3D imaging
     
Detailed Description
     
   

Recent technological innovations, eg detection and acquisition hardware, have pushed sparse-photon imaging to the fore in a variety of applications including 3D Lidar imaging and microscopy. 3D Lidar imaging consists in sending laser pulses to a target and capturing the returned photons after reflection from the target. Recent advances in single-photon detectors allowed the use of such systems to acquire 3D images in low photon regime (few received photons) due for example to long-range km imaging or fast imaging, which constitute important challenges for automotive Lidar and sensing for autonomous vehicles. Despite recent advances, current systems can still be optimized regarding the task to be achieved such as parameters estimation, classification, etc.

 

This project deals with two main challenges: (i) dealing with imaging in extreme conditions due to imaging through obscurants (high noise levels) or sparse photon imaging (low illumination imaging), (ii) dealing with the high volume of data (e.g., multimodal imaging, fusion of different sensors, 3D videos). In this context, the PDRA will work on the development of new strategies to improve both the acquisition and processing of single-photon data. A focus will be on statistical based methods that allows fast data processing, while providing uncertainty measures about the estimates. The candidate will also investigate hybrid methods combining statistical methods with state-of-the-art machine learning algorithms to solve challenging imaging problems, e.g., multi-sensor fusion, inverse problems.

The PDRA will work within Heriot-Watt and the wider community via the EPSRC Quantum Technology Hub in Quantum Imaging (Quantic). The successful candidate will have the opportunity to work with the UK’s top researchers in these fields via the Hub’s extensive academic and industrial partners.

The contract is for an initial 24-month period, with the possibility for an extension beyond the original contractual period.

The ideal candidate will develop methods that are

 

·Statistical based methods that use advanced Bayesian modelling to obtain robust algorithms, fast performance and uncertainty measures on high-dimensional data

·Based on optimization for fast processing and/or sampling methods for uncertainty measures

·Be familiar with solving inverse problems with different tools, including hybrid methods combining state-of-the-art tools to benefit from the strength of each tool (plug-and-play methods with machine learning)

 

     
Key duties and responsibilities
     
   

 

·Develop a general statistical framework and new computational solutions as detailed above.

 

·Write research reports and publications in peer reviewed journals and conferences, and/or other appropriate media. Analyse and interpret the results of own research and generate original ideas bases on outcomes. Prepare proposals for own or joint research and applications to external bodies, e.g. for funding purposes. Use initiative and creativity to identify areas for research, develop new research methods and extend the research portfolio.

 

·Assist the development of student research skills, and be expected to contribute to the assessment of student knowledge (particularly PhD students) in the context of teaching and supervision duties.

 

·Build internal contacts and participate in internal networks for the exchange of information and to form relationships for future collaboration. Work with academic colleagues on areas of shared research interest and contribute to collaborative decision making. Join external networks to share information and identify potential sources of funds.

 

·Provide guidance as required to support staff, research students and any other students who may be assisting with the research.

 

·Contribute, under supervision, to the planning of research projects, including the development of new grant/contract proposals. Make internal and external contacts to develop knowledge and understanding and form relationships for future collaboration.

 

·We are looking for a creative and highly motivated researcher willing to work as part of a team.

 

 

·Good communication skills and an appropriate publication record are essential.

 

·General tasks will involve scientific research; analysis and interpretation of data; communication with other investigators involved in this collaborative project; preparation of scientific papers; presentation of research at conferences.

 

·The successful candidate will be expected to conduct and lead their own research whilst also supervising the activities of junior group members and PhD students.

 

·Responsibilities will also include assistance liaising with companies and external collaborators.

 

·The successful candidate is also expected to be involved in our outreach activities, with roles that can be tuned to the specific preferences of the candidate but will involve for example interviews, talks for the general public and preparation of experimental demonstrators.

     
Education, qualifications and experience
     
   

Essential Criteria

·Be familiar with Matlab, and Python,

·Experience in solving inverse problems using statistical modelling (such as Bayesian inference), and different algorithms (such as optimization, stochastic and hybrid plug-and-play methods)

·Experience of working in a Higher Education or similar environment.

·Applicants should hold a PhD in a relevant area of Physics, Electrical Engineering, or Mathematics (or a thesis submitted by the start date of the project).

·A record of high quality publications, and evidence of contribution to the writing of these publications proportionate to opportunity.

·Appropriate publication record for stage in career.

·Must have proven academic ability and a demonstrable high level of technical competence in the analysis / modelling of the results and in developing suitable computational methods.

·Strong theoretical understanding and thorough grounding in methods relevant to the project.

·Ability to articulate research work, both in technical reports / papers and by oral presentation.

·Ability to formulate and progress work on their own initiative.

·Evidence of research ability: problem solving, flexibility.

·Must be able to work as part of a team on the experiments at Heriot-Watt and more widely with the collaborators at other Universities. An ability to travel widely is desirable.

·Experience in writing and managing peer-reviewed papers.

·Experience in public presentations of scientific results (e.g. conference talks).

·Energy and enthusiasm for the project.

 

Desirable Criteria

·Be familiar with C and parallel programing tools (GPU)

·Evidence of ability to present work effectively in person, e.g. at conferences and seminars.

·Previous experience with one or more of the following experimental areas: Computational imaging; Machine Learning; Statistical Signal Processing; quantum enhanced imaging.

·Experience in leading the writing of scientific papers.

·Evidence of securing own funding.

·Evidence of ability, subject to opportunity, to guide other researchers, e.g. PhD students and undergraduate project students.

·Experience of research student supervision.

·Capability to be self-directed and think innovatively.

     
How To Apply
     
   

Applications can be submitted up to midnight (UK time) on 20 July 2020

At Heriot-Watt University we understand that being diverse makes us better which is why we support a culture of respect and equal opportunity, and value diversity at the heart of what we do. We want to increase the diversity of our workplace to underpin a dynamic and creative environment.

Use our total rewards calculator: https://www.hw.ac.uk/about/work/total-rewards-calculator.htm to see the value of benefits provided by Heriot-Watt University.

     
Minimum Salary 32817
     
Maximum Salary 40322
     
Currency GBP
     
     
     
Amount of Travel

 

Dans cette rubrique

(c) GdR 720 ISIS - CNRS - 2011-2020.