PhD Candidate in AI-powered Digital Monitoring Systems for Small-Scale Fisheries in East Africa

Arbeidsgiver
NTNU - Norges teknisk-naturvitenskapelige universitet
Stillingstittel
PhD Candidate in AI-powered Digital Monitoring Systems for Small-Scale Fisheries in East Africa
Frist
20.08.2024
Ansettelsesform
Prosjekt

Beskrivelse

This is NTNU

NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The university is located in three cities with headquarters in Trondheim.

At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world.

You will find more information about working at NTNU and the application process here.


About the job

Work package 1 of the Asia-Africa Blue Tech Superhighway (COAST) project aims to develop digital information systems for effective management of small-scale fisheries in Kenya, Zanzibar and Tanzania. These fisheries are multi-species, geographically dispersed and exhibit flexible and dynamic fishing patterns. This makes data collection, stock assessment and data-informed management difficult. To address this, a high resolution near real-time digital catch monitoring system will be designed and implemented, including trackers to be installed on a selection of fishing vessels.

This PhD position will focus on improving the existing monitoring system, and develop dynamic maps of ocean conditions plus predictions of good fishing zones, based on catch and effort data plus partially simulated and partially measured oceanographic data. This system will furthermore be used to provide input to fisheries management though the use of AI methods and control theory.

The position reports to Associate Professor Morten Omholt Alver, morten.alver@ntnu.no , who will be the main supervisor. Prof. Damiano Varagnolo will be co-supervisor.


Duties of the position

For a position as a PhD Candidate, the goal is a completed doctoral education up to an obtained doctoral degree.

The PhD candidate will work on a range of challenging and interesting tasks:

  • Take part in an international and interdisciplinary consortium of researchers working towards the objectives of the COAST project.
  • Combine ocean model data with fisheries monitoring data through data assimilation and machine learning methods to provide useful information for fishers and management.
  • Make a contribution towards more efficient and sustainable small-scale fisheries.

Required selection criteria
  • You must have a professionally relevant background in two or more of the listed subjects: machine learning, control engineering, estimation theory, oceanography, ocean modelling, numerical analysis or statistics.
  • You should have experience in scientific computing within development environments such as Matlab and/or Python.
  • Your education must correspond to a five-year Norwegian degree program, where 120 credits are obtained at master's level.
  • You must have a strong academic background from your previous studies and an average grade from the master's degree program, or equivalent education, which is equal to B or better compared with NTNU's grading scale. If you do not have letter grades from previous studies, you must have an equally good academic basis. If you have a weaker grade background, you may be assessed if you can document that you are particularly suitable for a PhD education.
  • Master's students can apply, but the master's degree must be obtained and documented by the end of 2024.
  • You must meet the requirements for admission to the faculty's doctoral program (https://www.ntnu.edu/ie/research/phd).

The appointment is to be made in accordance with Regulations on terms of employment for positions such as postdoctoral fellow, Phd candidate, research assistant and specialist candidate and Regulations concerning the degrees of Philosophiae Doctor (PhD) and Philosophiae Doctor (PhD) in artistic research at the Norwegian University of Science and Technology (NTNU).


Preferred selection criteria

Useful qualifications for candidates are:

• Machine learning
• Numerical modelling
• Physical and biological oceanography
• Control engineering
• Estimation theory
• Statistics
• Programming (e.g. Python, Matlab)
• Good written and oral English language skills.


Personal characteristics

In the evaluation of which candidate is best qualified, emphasis will be placed on education, experience and personal suitability, as well as motivation, in terms of the qualification requirements specified in the advertisement. The following personal characteristics are desired:

• Problem solver
• Focused on results
• Good communicator
• Willing to learn


We offer
  • exciting and stimulating tasks in a strong international academic environment
  • an open and inclusive work environment with dedicated colleagues
  • favourable terms in the Norwegian Public Service Pension Fund
  • employee benefits

Salary and conditions

As a PhD candidate (code 1017) you are normally paid from gross NOK 532 200 per annum before tax, depending on qualifications and seniority. From the salary, 2% is deducted as a contribution to the Norwegian Public Service Pension Fund.

The period of employment is 3 years.

Appointment to a PhD position requires that you are admitted to the PhD programme in Engineering Cybernetics within three months of employment, and that you participate in an organized PhD programme during the employment period.

The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants, and the acts relating to Control of the Export of Strategic Goods, Services and Technology. Candidates who by assessment of the application and attachment are seen to conflict with the criteria in the latter law will be prohibited from recruitment to NTNU.

After the appointment you must assume that there may be changes in the area of work.

It is a prerequisite you can be present at and accessible to the institution on a daily basis.


About the application

The application and supporting documentation to be used as the basis for the assessment must be in Norwegian or English.

Publications and other scientific work must follow the application. Please note that your application will be considered based solely on information submitted by the application deadline. You must therefore ensure that your application clearly demonstrates how your skills and experience fulfil the criteria specified above.

The application must include:

  • CV and certificates
  • transcripts and diplomas for bachelor's and master's degrees. If you have not completed the master's degree, you must submit a confirmation that the master's thesis has been submitted.
  • A copy of the master's thesis. If you recently have submitted your master's thesis, you can attach a draft of the thesis. Documentation of a completed master's degree must be presented before taking up the position.
  • If you have publications or other relevant research work, include these.

If all, or parts, of your education has been taken abroad, we also ask you to attach documentation of the scope and quality of your entire education, both bachelor's and master's education, in addition to other higher education. Description of the documentation required can be found here. If you already have a statement from Norwegian Directorate for Higher Education and Skills, please attach this as well.

We will take joint work into account. If it is difficult to identify your efforts in the joint work, you must enclose a short description of your participation.

In the evaluation of which candidate is best qualified, emphasis will be placed on education, experience and personal and interpersonal qualities. Motivation, ambitions, and potential will also count in the assessment of the candidates.

NTNU is committed to following evaluation criteria for research quality according to The San Francisco Declaration on Research Assessment - DORA.


General information

Working at NTNU

NTNU believes that inclusion and diversity is our strength. We want to recruit people with different competencies, educational backgrounds, life experiences and perspectives to contribute to solving our social responsibilities within education and research. We will facilitate for our employees’ needs.

NTNU is working actively to increase the number of women employed in scientific positions and has a number of resources to promote equality.

The city of Trondheim is a modern European city with a rich cultural scene. Trondheim is the innovation capital of Norway with a population of 200,000. The Norwegian welfare state, including healthcare, schools, kindergartens and overall equality, is probably the best of its kind in the world. Professional subsidized day-care for children is easily available. Furthermore, Trondheim offers great opportunities for education (including international schools) and possibilities to enjoy nature, culture and family life and has low crime rates and clean air quality.

As an employee at NTNU, you must at all times adhere to the changes that the development in the subject entails and the organizational changes that are adopted.

A public list of applicants with name, age, job title and municipality of residence is prepared after the application deadline. If you want to reserve yourself from entry on the public applicant list, this must be justified. Assessment will be made in accordance with current legislation. You will be notified if the reservation is not accepted.

If you have any questions about the position, please Associate Professor Morten Omholt Alver, email: morten.alver@ntnu.no . If you have any questions about the recruitment process, please contact HR Consultant Berit Dahl, e-mail: berit.dahl@ntnu.no .

If you think this looks interesting and in line with your qualifications, please submit your application electronically via jobbnorge.no with your CV, diplomas and certificates attached. Applications submitted elsewhere will not be considered. Upon request, you must be able to obtain certified copies of your documentation.

Application deadline: 20.08.2024.


Sektor
Offentlig
Sted
Høgskoleringen 1, 7491 Trondheim
Stillingsfunksjon
Forskning/Stipendiat/Postdoktor, Annet, Ingeniør
FINN-kode
363300943
Sist endret
31. juli 2024 06:16