The Norwegian University of Science and Technology (NTNU) is inviting applications for a fully funded PhD Candidate position in Structure-preserving Generative Modeling. This research position focuses on advancing machine learning and generative artificial intelligence frameworks by integrating mathematical structures and physical constraints.
Position Overview
| Program / Position | PhD Candidate (Fellowship) |
|---|---|
| Host Institution | Norwegian University of Science and Technology (NTNU) |
| Research Area | Structure-preserving Generative Modeling, Applied Mathematics, Machine Learning |
| Location | Trondheim, Norway |
| Job Ref ID | 299879 |
| Application Deadline | Check official portal (Typically 3-4 weeks from posting) |
| Application Link | Apply Online via Jobbnorge |
Designation
PhD Candidate / Doctoral Research Fellow
Research Area
The successful applicant will conduct research in the intersection of computational mathematics, scientific machine learning, and generative modeling. Key research topics include:
- Development of novel generative models (e.g., diffusion models, flow matching, VAEs) that preserve geometric, physical, or algebraic structures.
- Integration of differential equations and geometric mechanics into deep learning architectures.
- Applications to physical sciences, dynamical systems, and engineering problem domains.
Scholarship & Position Description
The PhD fellowship is a fully funded research position under the standard Norwegian academic employment model. PhD candidates at NTNU are employed as staff members with social security benefits, pension contributions, and competitive salaries.
- Appointment Duration: 3 years of pure research (or 4 years with a 25% teaching/departmental duty component).
- Salary: Remunerated according to the Norwegian State Salary Scale for PhD candidates (code 1017), with standard tax and pension deductions.
- Work Environment: Collaborative research environment with access to high-performance computing facilities and international research networks.
Eligibility and Qualifications
Applicants must satisfy the requirements for admission to the doctoral program at NTNU:
- Educational Background: A Master’s degree (or equivalent 120 ECTS) in Applied Mathematics, Computer Science, Computational Science, Statistics, Physics, or a closely related quantitative field.
- Academic Performance: Strong academic record with a weighted average grade of B or higher on NTNU’s grading scale (or equivalent).
- Technical Skills: Strong background in mathematical analysis, linear algebra, numerical methods, and modern deep learning frameworks (PyTorch, JAX, or TensorFlow).
- Language Proficiency: Excellent written and oral English communication skills.
How to Apply
Applications must be submitted electronically through the Jobbnorge application portal. Please ensure all documentation is uploaded in English:
- Cover letter detailing your research interests and motivation for this specific project.
- Comprehensive Curriculum Vitae (CV).
- Transcripts and diplomas for both Bachelor’s and Master’s degrees.
- A copy of the Master’s thesis or relevant academic publications/preprints (if available).
- Contact details of 2–3 academic references.
Application Link & Details
Interested candidates can review the full details and submit their application through the official Jobbnorge platform:
Apply Now for the NTNU PhD Position (Job Ref: 299879)
