Postdoctoral Position in Automated Planning and Execution on Autonomous Marine Robotic Platforms
The position’s field of research/research project
This Postdoctoral position is related to a highly interdisciplinary project which targets fundamental research questions in the fields of Autonomous control, and Oceanography. The project aims to image, process and analyze plankton images taken from the upper water column controlled by an embedded automated planning/execution system on an autonomous underwater vehicle (AUV), for goal driven commanding.
The Postdoctoral position entails significant knowledge and experience with Automated Planning and Execution and how it ties into deliberation embedded on an AUV. It will build upon existing capability in decision-making architectures such as the Teleo-Reactive EXecutive (T-REX) which has a space borne legacy from two NASA missions, one in deep space, the other on the surface of Mars. The research will entail building new search methods for plan synthesis and execution, extending these search methods towards anomaly detection and response as well as building domain models for automated planning which tie into Statistical Sampling methods as well as low-level control.
The successful candidate will be appointed for a period of 3 years.
Successful applicants must within the period of employment must have
- a PhD in computer science, artificial intelligence, mathematics, or a similar field with a solid background in mathematics – the PhD should have been completed within the last 5 years at most
- Extensive programming experience in C/C++, Python and Matlab
- Demonstrated ability to translate deep theory into practice
- A solid publication track record in peer-reviewed journals and conferences
- A background in robotics and/or control would be a distinct advantage.
- A keen appreciation of upper water column biology will be a plus.
- The candidate must be willing and able to go to sea extensively and work in the field.
This position is within a highly interdisciplinary group – the candidate as a result must be able to articulate her/his ideas clearly and be open to those well outside her/his comfort zone.
Applicants will be required to justify their candidacy by explicitly explaining their personal motivation and academic aptitude for this position and its interdisciplinary nature. Applicants that expect to complete their PhD by early Summer 2018 can apply.
Academic results, publications, relevant specialization, work or research experience, personal qualifications, motivation and a desire to make an impact on critical societal problems will be considered when evaluating the applicants.
Excellent English skills, written and spoken, are required. Applicants from non-European or North American countries where English is not the official language must present an official language test report. The following tests can be used as such documentation: TOEFL, IELTS or Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). Minimum scores are:
- TOEFL: 600 (paper-based test), 92 (Internet-based test)
- IELTS: 6.5, with no section lower than 5.5 (only Academic IELTS test accepted)
- CAE/CPE: grade B or A
Appointments will be made in accordance with current university regulations. The successful applicant must agree to the conditions laid down for public employees and must sign a contract regulating the starting date and the duration of the employment.
The position follows code 1352, salary grade range from 57 in the Norwegian State salary scale, gross NOK 490 900 per year, depending on qualifications. A deduction of 2% is made as a statutory contribution to the Norwegian Public Service Pension Fund.
The main supervisor will be Professor Kanna Rajan (Kanna.Rajan@ntnu.no) at the Department of Engineering Cybernetics, with co-supervision by Professor Annette Stahl (email@example.com), Professor Geir Johnsen and Professor Nicole Aberle-Malzahn at the Department of Biology. The research activity will be associated with the Center of Excellence on Autonomous Marine Operations and Systems (AMOS) at NTNU (https://www.ntnu.edu/amos ).
NTNU can offer an informal and friendly workplace with dedicated colleagues, academic challenges and attractive schemes for home loans, insurance and pensions in the Norwegian Public Service Pension Fund.
Further details about the position can be obtained from Professor Kanna Rajan, e-mail: Kanna.Rajan@ntnu.no .
The Faculty of Information Technology and Electrical Engineering wants to attract outstanding and creative candidates who can contribute to our ongoing research activities. We believe that diversity is important to achieve a good, inclusive working environment. We encourage all qualified candidates to apply, regardless of the gender, disability or cultural background.
Under Section 25 of the Freedom of Information Act, information about the applicant may be made public even if the applicant has requested not to have his or her name entered on the list of applicants.
Applicants should send the following as part of their application:
- A letter of motivation explicitly targeting this position which does not exceed one page
- A half page description of their PhD dissertation
- A current academic CV
- A diploma supplement or a similar document, which describes in detail the study and grading system and the rights for further studies associated with the obtained degree
- Any relevant certified copies of diplomas and certificates
- Links to code samples in Github or other repositories
The application must be sent electronically via this page with the above information (all in one combined PDF file).
Mark the application IE 065-2018.
Deadline for applications: 2018-04-26.
About this job
- Deadline Thursday, April 26, 2018
- Employer NTNU - Norwegian University of Science and Technology
- Municipality Trondheim
- Place of service Trondheim
- Jobbnorge ID 150721
- Internal ID 2018/10526
- Scope Fulltime
- Duration Project
- Applications on this job are registered in an electronic form on jobbnorge.no
- You must complete: Standard CV
- Please refer to where you first saw this job advertised!