Sort by
Refine Your Search
-
the experimental team co-supervise BSc and MSc student projects As part of the Danish PhD program, you will also take PhD courses, participate in teaching, conduct an external research stay, and disseminate your
-
Present and discuss research findings to both peers and the public Assist in teaching courses and co-supervise MSc/BSc students with relevant projects Visit and collaborate with research partners in Denmark
-
will work closely with members of our research group, as well as with other research groups at DTU National Food Institute. You will also be involved in teaching Bachelor and Master students within our
-
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
-
. 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
-
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 Prof. Niels
-
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
-
approaches for the computational analysis of time-resolved data on reactions, contribute to teaching and supervising BSc and MSc student projects Qualifications You must have a two-year master's degree (120
-
. 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 applicants will be made by
-
of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment of the applicants will be conducted by Associate Professor Georgios Tsaousoglou and Head of Section Razgar