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PhD Candidate in Digital Twins for Wind Farms
4 months ago
About the job
For a position as a PhD Candidate, the goal is a completed doctoral education up to an obtained doctoral degree.
We have a vacancy for a PhD Candidate within wind and digital twin areas at the .
We are seeking a highly motivated PhD candidate to join our team in the project of “Digital twin for forecasting of power production to wind energy demand”. The successful candidate will work closely with a multidisciplinary team to research, develop and implement innovative solutions to accelerate the transition to renewable energy. The proposed position is linked to the project TWINVEST (Universal, open-source and cybersecure Digital Twin to provide investors in onshore wind farms valuable insights about current operations and future investments) funded under the EC’s HORIZON-CL5-2023-D3-02-14 initiative.
Your immediate leaders are your supervisors and the Head of the Department.
Duties of the position
Conduct original, cutting-edge research, including critical literature review to identify the state-of-the-art and research gaps, designing research projects and methodologies, and generating, collecting, and analysing data. Work with the project partners and contribute to the development of digital twin framework and architecture for onshore wind energy. Contribute to the dissemination of research in the form of scientific publications, project reports, etc. Contribute to the activities of the research group in collaboration with other researchers. Testing and validation via interpretation of data from laboratory-scale to full-scale.
Required selection criteria
You must have a professionally relevant background in applied mathematics, cybernetics, or engineering. Strong knowledge in wind energy sector with wind energy domain knowledge especially in modelling, sitting, sizing and wake effect knowledge, digital twin technology with embedded decision support and optimization. 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 . 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 01.07.2024 You must meet the requirements for admission to the faculty's doctoral program () Excellent English skills (both written and spoken) Applicants from non-English speaking countries outside Europe must present an official language test report. The acceptable tests are TOEFL, IELTS, and Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). Minimum scores are:TOEFL: 600 / writing 4.5 (paper-based) or 92 / writing 22 (internet-based)IELTS: 6.5, with no section lower than 5.5 (only Academic IELTS test accepted)CAE/CPE: grade B or A.------------------
The appointment is to be made in accordance with and
Preferred selection criteria
Knowledge and experience within digital twin and modelling in wind energy areas, and optimization are favorable and should be highlighted. Strong modeling skills/experience with both mathematical- and data-driven models. Academic results, publications, relevant specialization, work or research experience, personal qualifications, and motivations for making an impact on future renewable energy will be considered when evaluating the applicants. Documented work experience from industry (optional).
Personal characteristics
Be scientifically curious and open to new research challenges, including consideration of a sustainable future. Demonstrate independence and persistence in addressing and solving technical problems. Be flexible and reliable, with ability to work effectively independently and as part of a team. Ability to travel to cooperate in industry and other research partners. Open to feedback and input from others as well as able to respect, collaborate, and negotiate with others.Emphasis will be placed on personal and interpersonal qualities.
We offer
exciting and stimulating tasks in a strong international academic environment an open and with dedicated colleagues favourable terms in the
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 within three months of employment, and that you participate in an organized PhD programme during the employment period.
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