PhD Research Fellow in Machine Learning/Signal Processing for Planetary Ground Penetrating Radar

PhD Research Fellow in Machine Learning/Signal Processing for Planetary Ground Penetrating Radar

About the position

Position as PhD Research Fellow in Machine Learning/Signal Processing for Planetary Ground Penetrating Radar available at the Centre for Space Sensors and Systems (CENSSS) (https://www.mn.uio.no/censss/english/index.html) at the Department of Technology Systems (ITS) (https://www.mn.uio.no/its/english/).

CENSSS is a Centre for researched based innovation (SFI) at the Department of Technology Systems at Kjeller. The Centre is funded by the Norwegian Research Council and the University of Oslo.

No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo.

Starting date is as soon as possible.

The fellowship period is 3 years.

A fourth year may be considered with a workload of 25 % that may consist of teaching, supervision duties, and/or research assistance. This is dependent upon the qualification of the applicant and the current needs of the department.

Knowledge development in a changing world - Science and technology towards 2030.

The Faculty of Mathematics and Natural Sciences

Job description

The PhD fellow will be part of the RIMFAX team on the NASA Mars 2020 Perseverance rover mission. RIMFAX is a Ground Penetrating Radar (GPR) and one of seven scientific instruments aboard the Perseverance rover. The RIMFAX Science team is an international team with participants from institutions in both US and Europe, see: https://mars.nasa.gov/mars2020/spacecraft/instruments/rimfax/ (https://science.nasa.gov/mission/mars-2020-perseverance/science-instruments/#sensors).

The main goal of the RIMFAX experiment is to study the environmental and geological history of Mars at the Perseverance landing site in Jezero crater.

The PhD research work will include one or more of the following topics and tasks:

• Algorithms and methods for optimal imaging of the geological structures of interest
• Machine learning methods for automatic interpretation/classification of the RIMFAX radar images
• Retrieval of geophysical parameters, such as dielectric properties, from RIMFAX data
• Dissemination through scientific publications

Qualification requirements

The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe's leading communities for research, education and innovation. Candidates for these fellowships will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials.

• Master's degree or equivalent in Geoscience, Physics or Computer Science
• Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system
• Must have experience in one or more of the following topics; Signal Processing, Machine Learning or Geophysics
• Must have good programming skills in Python
• Fluent oral and written communication skills in English

The research area for the position can include technologies or infor-mation referred to in the Ministry's export control regulations or the Norwegian National Security Act (Lov om Nasjonal Sikkerhet, a.k.a. “Sikkerhetsloven"), and the candidate must be eligible for a Norwegian security clearance.

Grade requirements:
The norm is as follows:

• The average grade point for courses included in the Bachelor's degree must be C or better in the Norwegian educational system
• The average grade point for courses included in the Master's degree must be B or better in the Norwegian educational system
• The Master's thesis must have the grade B or better in the Norwegian educational system
• English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements:

https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 (https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8)

The purpose of the fellowship is research training leading to the successful completion of a PhD degree.

The fellowship requires admission to the PhD programme at the Faculty of Mathematics and Natural Sciences. The application to the PhD programme must be submitted to the department no later than two months after taking up the position.

For more information see:

http://www.uio.no/english/research/phd/ (http://www.uio.no/english/research/phd/)

http://www.mn.uio.no/english/research/phd/ (http://www.mn.uio.no/english/research/phd/)

Personal skills

• Ability to take initiative and come up with new ideas to solve theoretical and practical problems
• Ability to work both independently and as part of a team
• Good communication skills

We offer

• Salary NOK 532 200 - 575 400,- per annum depending on qualifications and seniority as PhD Research Fellow (position code 1017)
• Attractive welfare benefits (https://www.uio.no/english/for-employees/employment/welfare/index.html) and a generous pension agreement
• Vibrant international academic environment
• Career development programmes (https://www.mn.uio.no/english/research/phd/career-support/index.html)
• Oslo's family-friendly surroundings with their rich opportunities for culture and outdoor activities

How to apply

The application must include:

• Cover letter - statement of motivation and research interests
• CV (summarizing education, positions and academic work - scientific publications)
• Copies of the original Bachelor and Master's degree diploma and transcripts of records
• Letters of recommendation
• Documentation of English proficiency if applicable
• List of publications and academic work that the applicant wishes to be considered by the evaluation committee
• Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number)

The application with attachments must be delivered in our electronic recruiting system (please follow the link “Apply for this job"). Foreign applicants are advised to attach an explanation of their University's grading system. Please note that all documents should be in English or a Scandinavian language.

Interviews with the best qualified candidates will be arranged.

Formal regulations

Please see the guidelines (https://www.uio.no/english/about/regulations/personnel/academic/guidelines-appointment-postdoc-researcher.html) and regulations (https://www.uio.no/english/about/regulations/personnel/academic/regulations-employment-conditions-postdoc.html) for appointments to Research Fellowships at the University of Oslo.

According to the Norwegian Freedom and Information Act (Offentleglova) information about the applicant may be included in the public applicant list, also in cases where the applicant has requested non-disclosure.

UiO has an agreement for all employees (https://www.uio.no/english/for-employees/employment/work-results/agreement-rights-to-work-results.html), aiming to secure rights to research results a.o.

Inclusion and diversity are a strength. The University of Oslo has a personnel policy objective of achieving a balanced gender composition. Furthermore, we want employees with diverse professional expertise, life experience and perspectives.

If there are qualified applicants with disabilities, employment gaps or immigrant background, we will invite at least one applicant from each of these categories to an interview.

Contact information

For further information about the position, please, contact:

Professor Svein-Erik Hamran, phone: +47 22842211, e-mail: s.e.hamram@its.uio.no

Senior advisor Tor Berger, phone: +47 22842212 , e-mail: tor.berger@its.uio.no

For technical questions regarding Jobbnorge, please, contact:

HR Adviser Olga Holmlund, e-mail: olga.holmlund@mn.uio.no