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PhD Fellowship position in Quantum-Inspired Evolutionary Algorithm for Multi-Objective Integrative Optimization

Oslo Metropolitan University is Norway's third largest university with almost 22,000 students and over 2,500 employees. We have campuses in central Oslo and at Romerike. OsloMet educates students and conducts research that contributes to the sustainability of the Norwegian welfare state and the metropolitan region.

The Faculty of Technology, Art and Design (TKD) offers higher education and research and development (R&D) activities within technical subjects, arts and design. The Faculty has approximately 4.000 students and 400 staff members and is situated at Pilestredet Campus in downtown Oslo and at Kjeller Campus in Viken.

The Department of Computer Science offers three bachelor’s degree programmes, a master’s degree programme, and is part of a cross-departmental PhD program. Academic staff at the department are pursuing research in a wide range of areas including computer science, the natural sciences, and innovation and management. Both students and researchers are also involved in an increasing number of interdisciplinary initiatives across the university.

The Department of Computer Science at the Faculty of Technology, Art and Design (TKD) has a vacant PhD Fellowship position in the field of artificial intelligence with quantum computing. The project combines evolutionary algorithms (EAs) with quantum computing, focusing on its application in complex multi-objective optimization problems. The PhD candidate will be part of the Artificial Intelligence academic group.  

Area of research

The primary objective of this project is to formulate and implement a multi-objective quantum-inspired EAs (QEA) tailored specifically for classical computers, with a focus on addressing the prevalent challenges in the domain of multi-objective integrative optimization (MIO) problems.  Real-world optimization problems, prevalent in industries, are often complex, involving different interrelated optimization problems with multiple interconnected and conflicting objectives. Most of these involved independent optimization problems are interrelated, and combining them into a global integrative optimization problem is therefore necessary. This proposal considers formulating an MIO problem by combining k optimization problems, resulting in k objective functions. As a result, instead of seeking a single solution, the approach is to provide a set of alternatives (Pareto-optimal front) that reflect the trade-off between the objectives resulting from the MIO, allowing decision-makers to choose based on their preferences. This practical approach is expected to significantly enhance the decision-making process in industries.

The MIO problems inherently fall within the NP-hard class, and traditional optimization methods often cannot handle the complexity of such real-world MIO problems, resulting in suboptimal solutions and long computational times. Evolutionary Algorithms (EAs), inspired by natural selection processes, have demonstrated effectiveness in handling NP-hard problems due to their stochastic nature, population-based exploration, and global search capabilities. However, issues like premature/slow convergence and imbalanced exploration-exploitation trade-offs limit their performance.

Recently, the emergence of quantum-inspired EAs (QEAs) has opened up new avenues for enhancing the effectiveness of EAs by striking a better balance between exploration and exploitation. Drawing inspiration from quantum mechanics, QEAs integrate concepts such as superposition, quantum parallelism, entanglement, interference, coherence, and measurement into the existing EA framework. Recent advancements have underscored the significant advantages of QEAs over classical EAs, demonstrating success in solving complex NP-hard problems that were previously deemed computationally intractable for classical computers. However, existing QEAs are typically designed for single optimization problems and exhibit optimal efficiency on specialized quantum hardware rather than classical computers. They also encounter challenges in maintaining coherence and leveraging entanglement for efficient exploration, necessitating further exploration of quantum operators and encoding schemes that can adapt to diverse problem structures and objective functions.

This project aims to bridge this gap by developing a novel multi-objective QEA that is specifically designed for classical computing environments. By utilizing quantum-inspired techniques, the objective is to provide industries with a practical and efficient solution for tackling real-world complex multi-objective optimization challenges in areas such as manufacturing and logistics. This research goal encompasses both theoretical and practical dimensions, focusing on contributing significantly to developing multi-objective QEA. Ultimately, the goal is not just to advance optimization methodologies but to facilitate broader access to cutting-edge problem-solving techniques in academic and industrial settings, thereby revolutionizing the way we approach and solve complex optimization problems.

The position is advertised as a 3-year position with 100% research, or a 4-year position with 75% research and 25% other tasks (teaching, supervision and/or administrative work). The goal must be to complete the PhD program/degree within the decided time frame. The decision on a 3- or 4-year position will be discussed as part of the interviews in the hiring process.  

Qualification requirements and conditions

The following grade requirements are a condition for employment in the position:

Admission to the doctoral program in Engineering Science at the Faculty of Technology, Art and Design within three months of employment is a prerequisite for the position. If you already have a doctorate in a related field, you will not qualify for the position.

In assessing the applicants, emphasis will be placed on the department's overall needs and the applicant's potential for research within the field.

General criteria for employment in academic positions are covered by the Regulations on employment conditions for positions such as postdoctoral fellow, scientific assistant and specialist candidate.

Preferred selection criteria

Personal suitability will be emphasised.

It is important to OsloMet to reflect the population of our region, and all qualified candidates are welcome to apply. We make active endeavours to further develop OsloMet as an inclusive workplace and to make adaptations to the workplace where required. You are also welcome to apply for a position with us if you have had periods where you have not been in employment, education or training.

We can offer you

Practical information about relocation to Oslo and living in Norway (


To be considered for the position, you must upload the following documents by the application deadline:

The following language tests are approved documentation: TOEFL, IELTS, Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). In these tests, you must have achieved at least the following scores:

We only process applications sent via our electronic recruitment system and all documents must be uploaded for your application to be processed. The documents must be in English or a Scandinavian language. Translations must be authorized. You must present originals at any interview. OsloMet checks documents, so that you as a candidate will get a real evaluation and fair competition.  

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. A background check may be conducted to verify information in submitted CVs and available documents. Background checks are not conducted without the consent of the applicant and relevant applicants will receive further information about this.

Other information

If you would like more information about the position, feel free to contact:

The position is paid according to the pay scale for Norwegian state employees, position code 1017 PhD fellow, NOK 532 200 per year.

If you have documents that cannot be uploaded electronically, please contact 

If you would like to apply for the position, you must do so electronically through our recruitment system.

Deadline for applications: August 1st 2024

Ref.: 24/19732

OsloMet is a Charter & Code certified institution by the EU Commission holding the right to use the logo HR Excellence in Research (HRS4R). OsloMet is a member of the EURAXESS network supporting a positive work environment for researchers in motion.

OsloMet has signed The Declaration on Research Assessment (DORA). DORA recognizes the need to improve the ways in which the outputs of scholarly research are evaluated.

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 are seen to be in conflict with the criteria in the latter law will not be considered for the position.

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