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reference: 4940009

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stillingsbetegnelse:
Postdoc in Deep Learning with a View to Remote Sensing and Ice Charting

jobbeskrivelse:
DTU Compute's Section for Image Analysis and Computer Graphics, invites applications for a 2-year postdoc position starting 1 March 2019. The position is financed by a project funded by Innovation Fund Denmark, 'Automated Downstream Sea Ice Products for Greenland Waters' - ASIP.

ASIP is a collaboration between the Danish Meteorological Institute (DMI), the National Space Institute (DTU Space), DTU Compute and Harnvig Arctic and Maritime aiming at developing automated sea ice products for Greenlandic waters to meet the increasing demands from a growing group of users operating in these waters.

The project aims at developing automated methods based on synthetic aperture radar (SAR) data and complementary satellite data to support handling of possible ambiguities in the SAR data.

In cooperation with faculty staff at DTU Compute and DTU Space, the successful candidate will collaborate with the external partners to obtain deep learning based products based on satellite data to give automated ice charts with much higher spatial and temporal resolution than offered by the present traditionally produced maps.

Research in the Section for Image Analysis and Computer Graphics is centered on advances in image analysis and computer graphics methods and algorithms which rely on developments in technology, where computing power has increased tremendously and new digital sensors and graphical processing units have allowed images to be recorded and rendered at an impressive rate, even on small handheld devices.

Besides photography, cameras and other image-generating sensors are used in a very wide range of applications. Various image-generating sensors are the basis for numerous medical diagnosis tools like computed tomography, medical resonance imaging, etc., allowing visualization of our body for precise diagnosis and treatment. Other application areas include industrial computer vision, life science, studies of material microstructure, and remote sensing. Most of our work is done in close collaboration with external partners from industry, medicine, materials science, or with other academics having image analysis problems.

DTU Compute is an internationally unique academic environment spanning the science disciplines mathematics, statistics and computer science. At the same time, we are an engineering department covering informatics and communication technologies (ICT) in their broadest sense. Finally, we play a major role in addressing the societal challenges of the digital society where ICT is a part of every industry, service, and human endeavour.

DTU Compute strives to achieve research excellence in its basic science disciplines, to achieve technological leadership in research and innovation, and to address societal challenges in collaboration with partners at DTU and other academic institutions, nationally and internationally, and, equally important, with industry and organizations. We communicate and collaborate with leading centres and strategic partners in order to increase participation in major consortia.

DTU Compute plays a central role in education at all levels of the engineering programmes at DTU - both in terms of our scientific disciplines and our didactic innovation.

Responsibilities and tasks
The main responsibilities and tasks will be the production of automated sea ice products based on the use of deep learning techniques such as convolutional neural networks (CNN) applied to multi-source satellite data. The successful candidate should live up to the following:

• You will be responsible for setting up deep learning based models to predict sea ice coverage and other relevant parameters.
• Your research will include selecting appropriate models for fulfilment of the overall project goal.
• You will contribute to reporting the results of the project to the funding party and in the international scientific literature.
• You should have the ability to motivate yourself and your colleagues to be at their best and to achieve the ambitious goals of the project.

Qualifications
Candidates should have a PhD degree in statistics, computer science, electrical engineering, or equivalent.

• You must be interested in and have documented experience in the application of deep learning and CNN methods to remote sensing related problems with a successful outcome.
• Knowledge of sea ice mapping procedures is an advantage.
• You must be able to handle of the large amounts of data involved.
• You should have documented experience in collaboration with scientific and/or industrial partners.

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and terms of employment
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union.The period of employment is two years.

The workplace will be DTU's main campus in Kongens Lyngby.

You can read more about career paths at DTU here. http://www.dtu.dk/english/about/job-and-career/working-at-dtu/career-paths

Further information
Further information may be obtained from Head of Section, Professor Anders Bjorholm Dahl, tel.: +45 4525 3907.

You can read more about DTU Compute at http://www.compute.dtu.dk. http://www.compute.dtu.dk/

Application procedure
Please submit your online application no later than 15 February 2019 (local time). To apply, please open the link "Apply online", fill out the online application form. The following must be attachedin English:

• Application (cover letter)
• CV
• Diploma (MSc/PhD)
• List of publications

Applications and enclosures received after the deadline will not be considered.

All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply.

DTU Compute has a total staff of 400 including 100 faculty members and 130 Ph.D. students. We offer introductory courses in mathematics, statistics, and computer science to all engineering programmes at DTU and specialised courses to the mathematics, computer science, and other programmes. We offer continuing education courses and scientific advice within our research disciplines, and provide a portfolio of innovation activities for students and employees.

DTU is a technical university providing internationally leading research, education, innovation and scientific advice. Our staff of 6,000 advance science and technology to create innovative solutions that meet the demands of society, and our 11,200 students are being educated to address the technological challenges of the future. DTU is an independent academic university collaborating globally with business, industry, government and public agencies.



numberOfPosts: 1

jobCategoriesCodes_0: http://data.europa.eu/esco/isco/C2310

abstractJV_contact_0: Please apply using one of the specified channels

positionTypeCode: directhire

contractTypeCodes_0: fulltime

Arbejdsgiver Navn: Danmarks Tekniske Universitet

source: DK-STAR