PhD scholarship in Deep Learning Theory and Differential Geometry – DTU Compute
2 months ago
Do you want to contribute to the understanding of modern deep learning by leveraging principles from differential geometry?
As our new PhD Student, your task will be to study modern deep learning approaches and develop a theoretical understanding based on differential geometry. In particular, deep neural networks perform surprisingly well on new unseen data, which is known as generalization. However, previous machine learning theory cannot fully explain this behavior and thus new approaches have emerged. A promising explanation is that during the training phase, the models are implicitly regularized which is attributed to the properties of the optimization technique. Intuitively, an example is that stochastic optimizers tend to find flatter minima in the complex loss landscape which is supposed to correlate with generalization. The behavior of the neural network also depends on the architectural choices and the additional training techniques applied during the learning phase. The goal of this project is to approach these concepts using differential geometry, providing a new theoretical framework and developing practical methodologies accordingly.
Qualifications
The nature of the project suggests that you should be interested in the mathematical and theoretical aspects of machine learning. Therefore, a sufficient background in mathematics (e.g., linear algebra, statistics, optimization, calculus) is expected, along with programming experience using deep learning frameworks in Python (e.g., PyTorch). While a background in machine learning and differential geometry is appreciated, it is not strictly required. Apart from the technical skills, you should be curious and motivated to learn new concepts.
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
.
Assessment
The assessment of the candidates will be made by Associate Professor Georgios Arvanitidis.
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. Starting date is 1 September 2024 according to the mutual agreement. The position is full-time.
You can read more about career paths at DTU here
.
Further information
Further information may be obtained from Georgios Arvanitidis, www2.compute.dtu.dk/~gear/.
You can read more about DTU Compute at www.compute.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 31 March 2024 (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:
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, race, disability, religion or ethnic background are encouraged to apply.
DTU Compute
DTU Compute is a unique and internationally recognized academic department with 385 employees and 11 research sections spanning the science disciplines mathematics, statistics, computer science, and engineering. We conduct research, teaching and innovation of high international standard – producing new knowledge and technology-based solutions to societal challenges. We have a long-term involvement in applied and interdisciplinary research, big data and data science, artificial intelligence (AI), internet of things (IoT), smart and secure societies, smart manufacturing, and life science. At DTU Compute we believe in a diverse workplace with a flexible work-life balance.
Section for Cognitive Systems
The position is in the Section for Cognitive Systems at DTU Compute, the Technical University of Denmark, which is an internationally renowned group for machine learning research, aiming for the highest quality research. Collaboration within the group and with other international groups is encouraged. Both salary and working conditions are excellent, and the group emphasizes a healthy work/life balance, while Denmark is known for high living standards. You can find more information at
Section for Cognitive Systems – DTU Compute
.
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.
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