PhD scholarship in Scientific Machine Learning - DTU Electro
Kgs. Lyngby, Denmark
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DTU - Technical University of Denmark
DTU er et teknisk eliteuniversitet med international rækkevidde og standard. Vores mission er at udvikle og nyttiggøre naturvidenskab og teknisk videnskab til gavn for samfundet.Are you interested in developing novel machine learning methodologies that are scalable, reliable and explainable and that can address imminent challenges?
Responsibilities and qualifications
As our new colleague in our research team your job will be to develop novel computational frameworks for machine learning. In particular, you will push the boundaries of
- Scalability, drawing upon recent large-scale capabilities in physics.
- Reliability, exploring uncertainty quantification and robust inference in machine learning.
- Explainability, leveraging identifiability and unique recovery explored using scientific machine leaning.
Machine learning, programming experience and a curious mind-set
You are fascinated by how computers can learn from data and you have a strong interest in the mathematical foundation of machine learning models. You will be responsible for developing scientific machine learning methodologies enabling new approaches for solving machine learning problems including reinforcement learning problems.
We are looking for a profile with the motivation and drive needed for making a difference that matters. You must bring an open mindset and like to create results via collaboration with multiple people working on similar problems with different professional and cultural backgrounds. You are therefore a talented, self-motivated, and team-oriented person who enjoys working on the theoretical foundation of machine learning. Your CV comprises:
- A strong relevant background within machine learning and mathematics.
- Extensive experience programming machine learning models.
- An active interest or experience in strong collaborations and interdisciplinary work at the intersection between machine learning, geophysics and acoustic data modeling.
- A strong experience with software defined radio Automatic Identification System (AIS) for ship detection.
- You must be fluent in English, both speaking and writing and possess excellent communication skills.
As part of the Danish Ph.D. program, you will follow a number of Ph.D. courses as well as take part in teaching and supervision of students. The PhD further includes interesting opportunities for an external research stay.
You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree.
Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education.
We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.
Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years.
You can read more about career paths at DTU here.
Further information
Further information may be obtained from Professor Peter Gerstoft (DTU Electro) pegers@dtu.dk
You can read more about DTU Electro at https://electro.dtu.dk/
If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark. Furthermore, you have the option of joining our monthly free seminar “PhD relocation to Denmark and startup “Zoom” seminar” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU.
Application procedure
Your complete online application must be submitted no later than 14 August 2025 (23:59 Danish time).
Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply now", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:
- A letter motivating the application (cover letter)
- Curriculum vitae
- Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale
You may apply prior to obtaining your master's degree but cannot begin before having received it.
Applications received after the deadline will not be considered.
All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply. As DTU works with research in critical technology, which is subject to special rules for security and export control, open-source background checks may be conducted on qualified candidates for the position.
Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear mission to develop and create value using science and engineering to benefit society. That mission lives on today. DTU has 13,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Engineering Machine Learning Mathematics ML models Open Source PhD Physics Reinforcement Learning Research Security Teaching
Perks/benefits: Career development Startup environment
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