Vacant PhD Fellowship position
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.
This is a 3-year position with 100% research, or a 4-year position with 75% research and 25% other career-advancing work. The goal is to complete the PhD program 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.
Applications are due May 1st.
Enhancing decision-making in industries
The primary objective of the project is to formulate and implement a multi-objective quantum-inspired EAs (QEA) tailored specifically for classical computers, focusing 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 provides 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 enhance the decision-making process in industries significantly.
Tackling multi-objective optimization challenges efficiently
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.
What OsloMet can offer you
- An exciting job opportunity at Norway’s third largest and most urban university
- Opportunities for professional development
- Beneficial pension arrangements with the Norwegian Public Service Pension Fund (spk.no/en/)
- Beneficial welfare schemes and a wide range of sports and cultural offers
- Free Norwegian language classes to employees and their partners/spouses
- Workplace in downtown Oslo with multiple cultural offers
Read more about criteria and the application process here!
If you would like more information about the position, feel free to contact:
- Head of the Group: Boning Feng, email: boning.feng@oslomet.no
- Associate Professor Kazi Shah Nawaz Ripon, email: kazi.ripon@oslomet.no ; Tel: +47 40 94 74 49