PhD Research Fellow in Informatics – (energy informatics, optimization and machine learning)

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PhD position in Informatics – (energy informatics, optimization and machine learning)

There is a vacancy for a PhD Research Fellow within Informatics – Energy Informatics at the Department of Informatics. The position is for a fixed-term period of 3 years with the possibility of a 4th year with compulsory other work (e.g. teaching duties at the Department). The position is subject to financing by the University of Bergen. The successful candidate must be able to start in the position no later than October 31st , 2024.

About the Department

Digitization of businesses, industry, public administration, and education makes informatics play an increasingly important role in the development of society. Research and education in informatics are crucial for the digital transformation of our society to succeed. The Department of Informatics contributes to this through eight research groups that deliver research and education at a high international level in algorithms, bioinformatics, information security, machine learning, optimization, programming theory, visualization and didactics. Our centers/labs Center for Data Science (CEDAS), Computational Biology Unit (CBU) and Energy Informatics Lab are important extensions of our research and education activities. The department offers education for the future at Bachelor, Master and PhD levels. The department is in rapid growth regarding its number of students, research directions, and employees. We have today about 1000 students, and 150 employees from over 35 countries, among which 37 are faculty and 50 PhD candidates.

About the project/work tasks

All employees are expected to contribute to excellence through high-quality research and teaching. The designated working environment for this position will be the Energy Informatics Lab in the Department of Informatics. Energy informatics is a specialized field within informatics that addresses challenges related to sustainable energy production, distribution, and conservation through the development and application of modern information and communication technology. This broad field incorporates methods from artificial intelligence, machine learning, optimization, high-performance computing, algorithms, computer security, and visualization. It finds applications in various sectors, including energy systems like wind energy and transportation. This project aims to bring together machine learning and optimization, combining their strengths to create advanced solutions for wind farms. For this position, we are looking for an outstanding candidate with experience and interest in operations research, reinforcement learning, and deep learning, along with a strong problem-solving mindset.

Qualifications and personal qualities

• The applicant must hold a master’s degree or equivalent education in computer science. Master students can apply provided they complete their final master exam before June 30th , 2024. It is a condition of employment that the master’s degree has been awarded.
• Research experience in machine learning is a requirement.
• Applicants must have excellent programming skills.
• Research experience in optimization methods is an advantage.
• Applicants must be able to work independently and in a structured manner and demonstrate good collaborative skills.
• Applicants must be proficient in both written and oral English.
• Personal and relational qualities will be emphasized. Research experience, ambitions and potential will also count when evaluating the candidates

Special requirements for the position

The University of Bergen is subjected to the regulation for export control system. The regulation will be applied in the processing of the applications.

About the PhD position

About the PhD Research Fellowship: The fellowship will be for a period of 3 years, with the possibility for a 4th year, consisting of 25 % compulsory work (e.g. teaching responsibilities at the department) distributed over the employment period. The 4th year is contingent on the qualifications of the candidate and the teaching needs of the department and will be decided by the head of department upon appointment.

The employment period may be reduced if you have previously been employed in a qualifying post (e.g. research fellow, research assistant).

About the research training: As a PhD Research Fellow, you must participate in an approved educational programme for a PhD degree within a period of 3 years. The deadline for applying for admission to the PhD programme at The Faculty of Mathematics and Natural Sciences is 2 months after you start your position or after the start of the research project that will lead to the PhD degree. It is a condition that you satisfy the enrolment requirements for the PhD programme at the University of Bergen

We can offer

• Exciting development opportunities as part of your role in a strong professional environment
• Salary as PhD research fellow (code 1017) in the state salary scale. This constitutes a gross annual salary of NOK 532 200 (equivalent to pay grade 54). Further promotions are made according to qualifications and length of service in the position. 
• Enrolment in the Norwegian Public Service Pension Fund
• Good welfare benefits

Your application must include

• A brief account of the applicant’s research interests and motivation for applying for the position
• The names and contact information for two reference persons. One of these must be the main advisor for the master’s thesis or equivalent thesis
• CV
• Transcripts and diplomas showing completion of the bachelor’s and master’s degrees. If you have not yet completed your master’s degree, please submit a statement from your institution confirming the expected date of award of your master’s degree. Your master’s degree must be documented with transcripts and/or diploma, alternatively a confirmation from your institution on completed degree and your grade, by June 30th , 2024.
• Relevant certificates/references
• Approved documentation of proficiency in English (if applicable: see requirements here)
• A list of any works of a scientific nature (publication list)
• Any publications in your name
• The application and appendices with certified translations into English or a Scandinavian language must be uploaded at Jobbnorge.

General information

Detailed information about the position can be obtained by contacting: Associate Professor Ahmad Hemmati or Associate Professor Nello Blaser or Head of Department Inge Jonassen.

For HR related matters, please contact Karoline Christiansen.

The state labour force shall reflect the diversity of Norwegian society to the greatest extent possible. People with immigrant backgrounds and people with disabilities are encouraged to apply for the position.

We encourage women to apply. If multiple applicants have approximately equivalent qualifications, the rules pertaining to moderate gender quotas shall apply.

  

The University of Bergen applies the principle of public access to information when recruiting staff for academic positions.

Information about applicants may be made public even if the applicant has asked not to be named on the list of persons who have applied. The applicant must be notified if the request to be omitted is not met.

The successful applicant must comply with the guidelines that apply to the position at all times.

For further information about the recruitment process, click here.

Life as a PhD candidate at UiB

Marion Claireaux tells about life and work as a PhD candidate at UiB.

About UiB

The University of Bergen is a renowned educational and research institution, organised into seven faculties and approximately 54 institutes and academic centres. Campus is located in the centre of Bergen with university areas at Nygårdshøyden, Haukeland, Marineholmen, Møllendalsveien and Årstad. 

There are seven departments and several centres at Faculty of Mathematics and Natural Sciences. Read more about the faculty and departments. 

Deadline: 2024-03-17 at 23:59
Unit: Engineering/it

Read the job description at the university homepage or apply.