Ph.D. Candidate in Reinforcement Learning for Project Scheduling Problems

Ntnu

Trondheim

Remote

NOK 522,000 - 638,000

Full time

3 days ago
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Job summary

NTNU's Department of Manufacturing and Civil Engineering invites applications for a PhD Candidate position focusing on Reinforcement Learning for Resource-Constrained Project Scheduling Problems (RCPSP). The successful candidate will pursue doctoral studies while contributing to high-quality research in digitalization of circular construction.

The position involves developing learning-based scheduling methods, extending them to uncertainty, publishing in top journals, and completing the PhD

Qualifications

  • A relevant master's degree in Computer Science/technology or equivalent (Norwegian five-year program).
  • Experience in reinforcement learning and graph neural networks (GNN).
  • Strong academic record with GPA equivalent to B or higher on NTNU's scale.
  • Fluent written and spoken English; provide evidence if not from Europe.

Responsibilities

  • Develop learning-based algorithms for deterministic scheduling problems.
  • Extend framework to scheduling under uncertainty.
  • Improve scalability, generalization, and computational performance.
  • Disseminate research outcomes through publications in peer-reviewed journals.
  • Complete the doctoral education and obtain a PhD.
  • Collaborate with PhD/post-docs and external partners.

Skills

Reinforcement learning
GNN
Programming
Artificial intelligence

Education

Master's degree in Computer Science/technology or equivalent (5-year Norwegian program)

Job description

The Department of Manufacturing and Civil Engineering has a vacancy for a

Ph.D. Candidate in Reinforcement Learning for Project Scheduling Problems

NTNU is a broad-based university with atechnical-scientific profile and a focusin 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 position

Are you motivated to take a step towards a doctorate and open up exciting career opportunities? As a PhD Candidate with us, you will work to achieve your doctorate, and at the same time gain valuable experience that qualifies you for a further career in higher education and research, in and outside academia.

The position will specificallyfocus on Reinforcement Learning for Resource-Constrained Project Scheduling Problem (RCPSP). The Ph.D.candidate will be a member of the group of Civil Engineering and Geomatics at NTNU and will tightly cooperate with other Ph.D./post-docs in projects (such as HEU-CIRCULess) and research groups at the department. The Ph.D. position will offer opportunities to develop high-quality research within the field of digitalization of circular construction.

Your immediate leader will be the Head of Department.

Duties of the position
  • Develop learning-based algorithms or methods for deterministic scheduling optimization problems with the aim of achieving competitive performance against state-of-the-art approaches.
  • Extend the developed framework to scheduling under uncertainty. Investigate how the proposed learning-based methods can be extended to uncertain and dynamic project environments.
  • Improve the scalability of learning-based scheduling methods and evaluate generalization, robustness, and computational performance.
  • Disseminate research outcomes. Publications in relevant high quality peer-reviewed journals are needed.
  • Complete the doctoral education until obtaining a doctorate
  • Carry out research of good quality within the framework described above
  • Academic publications and popular science dissemination

Be prepared for changes to your work duties after employment.

Required selection criteria
  • You must have a relevant master’s degree in Computer Scienceand technology, computer system engineering or equivalent. Your course of study must correspond to a five-year Norwegian course, where 120 credits have been obtained at master's level.
  • Experience in reinforcement learning, GNN, etc.
  • You must have a strong academic background from your previous studies and have an average grade from your Master's degree study, or equivalent education, which is equal to B or better compared to NTNU's grading scale . If you do not have letter grades from previous studies, you must have an equally good academic foundation. If you have a weaker grade background, you may be considered if you can document that you are particularly suitable for a PhD education.
  • Applicants must have fluent skills in both written and oral English. Non-English native speaker applicants who do not have masterin Europemust provide evidence of good English language skills, written and spoken. The following tests can be used as such documentation: TOEFL, IELTS or Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). Minimum scores are:TOEFL: 600 (paper-based test), 92 (Internet-based test); IELTS: 6.5, with no section lower than 5.5 (only Academic IELTS test accepted); CAE/CPE: grade B or A.
  • In extraordinary circumstances, formal documentation of language skills can be relinquished. In such cases, the candidate’s language skills will be assessed in a personal interview.
  • Experience in programming skills, and artificial intelligence.
Personal characteristics

To complete a doctoral degree (PhD), it is important that you are able to:

  • Work independently
  • The applicant must be motivated to work closely withteams and external partners
  • Work constructively under pressure or in the face of adversity
  • Show curiosity and strong motivation for the subject

Emphasis will be placed on personal qualities.

We offer
  • An exciting job with an important mission in society
  • Developing tasks in a strong and international professional environment
  • Open and inclusive working environment with committed colleagues
  • Free Norwegian language training at a basic level (A2)

We strive to attract employees with different skills, life experiences and perspectives to contribute to even better problem solving of our societal mission in research and education.

If you think this position is relevant and interesting, we encourage you to apply, regardless of gender, functional ability and cultural background, or whether you have been out of work for a period of time.

At NTNU we want to increase the proportion of women in scientific positions. We have a number of measures to promote equality.

Salary and conditions

In the position of PhD Candidate, code 1017, your gross salary will normally be NOK 580 000,-per annum depending on qualifications and seniority. A 2% statutory contribution to the State Pension Fund is deducted from the salary.

The employment period is 3 years for the doctoral work.

For employment as a PhD Candidate, it is a prerequisite that you gain admission to the PhD programme in Engineering https://www.ntnu.edu/studies/phiv within three months of your employment contract start date, and that you participate in an organized doctoral programme throughout the period of employment.

As an employee at NTNU, it is important that you keep yourself up to date with academic and organizational changes and adapt to them.

For the necessary professional and social interaction, it is a prerequisite that you are physically present and available to the institution on a daily basis.

The appointment is carried out in accordance with the principles of the State Employees Act , and Export control (legislation that regulates the export of knowledge, technology and services). Candidates who, after assessment of the application and attachments, are considered to bein conflict with the criteria in the latter act, will not be able to be employed.

About the application

The attachments (including a description of your scientific work) must accompany the application as these documents form the basis of the application assessment. The documents must be in English.

Please note: the application will only be assessed on the basis of the information we have received by the application deadline. Therefore, make sure that your application clearly shows how your skills and experience meet the criteria described above. The application and all attachments must be sent electronically via Jobbnorge.no. If you are invited to an interview, you must bring certified copies of certificates and diplomas upon request.

The application must include:

  • Transcripts for Bachelor's and Master's degrees
  • Diplomas for Bachelor's and Master's degrees
  • Copy of Master's thesis
  • Project outline containing proposals for an overall description of research questions, theoretical perspectives, methodological design for the project and progress plan (maximum 1500 words/4 pages)
  • Short letter of motivation (400 words/1 page)
  • Possibly publications etc. other relevant research work
  • Possibly certificates
  • CV
  • Names and contact information of three relevant referees

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. If your institution uses “diploma supplement” (normal for most European institutions), you must attach this. A description of the documentation required can also be found here . If you already have a statement from Norwegian Directorate for Higher Education and Skills (HK-dir) , please attach this as well.

Joint work will be considered. If it is difficult to identify your contribution to joint work, you must attach a brief description of your participation.

When assessing the best qualified, we emphasize necessary qualifications such as education, experience and personal suitability. Motivation for the position, ambitions, and potential for research will also count when assessing the candidates. NTNU recognizes a wide range of academic contributions and has committed itself to The San Francisco Declaration on Research Assessment and CoARA (responsible assessment of research and recognition of a greater breadth of academic contributions in accordance with NTNU's social mission).

General information

A public list of applicants with name, age, job title and municipality of residence is prepared after the application deadline. If you wish to be exempt 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 exemption is not granted.

If you have any questions about the position, please contact Yongping Liu (Associated professor), email yongping.liu@ntnu.no.

If you have any questions about the recruitment process, please contact HR Advisor Kristine Rognlid Hagaseth, e-mail: kristine.r.hagaseth@ntnu.no.

Gjøvik, a charming town by the shores of Lake Mjøsa, is known for its beautiful nature and rich cultural offerings. The town boasts a vibrant community with excellent schools, modern healthcare services, and a variety of recreational activities. With its strategic location, just a short drive from Oslo, Gjøvik combines the best of urban life and natural experiences. Here, you'll find a dynamic business environment and exciting career opportunities in a setting that values work-life balance.

NTNU - knowledge for a better world

NTNU - knowledge for a better world

The Norwegian University of Science and Technology (NTNU) creates knowledge for a better world and solutions that can change everyday life.

Department of Manufacturing and Civil Engineering

Our profile of expertise can help to solve the world’s most important societal challenge: the development of sustainable solutions in industry and society. This profile includes research on modern industrial processes, use of new and recycled materials, new technological solutions and the application of new forms of organization and business models. The Department of Manufacturing and Civil Engineering is one of eight departments in the Faculty of Engineering.

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