63 assistant-professor-and-data-visualization PhD positions at Technical University of Denmark in Denmark
Sort by
Refine Your Search
-
Tenure Track Researcher position in Sustainable and Healthy Food Systems. A researcher position in Denmark is equivalent to an Assistant Professor, with a stronger focus on project acquisition and a weaker
-
information may be obtained from Professor John Woodley, jw@kt.dtu.dk . You can read more about DTU Chemical Engineering at www.kt.dtu.dk . If you are applying from abroad, you may find useful information
-
the MSCA Doctoral Network CoDeF, with four of the PhD positions located in and around Copenhagen. More information on the CoDeF training network can be found here . Your main supervisor will be Professor
-
. You can read more about career paths at DTU here . Further information Further information may be obtained from Professor Lars Jelsbak, DTU Bioengineering, lj@bio.dtu.dk If you are applying from abroad
-
soon as possible thereafter. You can read more about career paths at DTU here . Further information Further information may be obtained from Associate Professor Maria Theresa Norn, DTU Entrepreneurship
-
information may be obtained from Associate Professor Ziwei Ouyang, ziou@dtu.dk . You can read more about DTU Electro at www.electro.dtu.dk . If you are applying from abroad, you may find useful information
-
paths at DTU here . Further information Further information may be obtained from Assoc. Professor Menghao Qin menqin@dtu.dk and Lei Fang lfan@dtu.dk You can read more about Department of Environmental
-
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 Adriano Sciacovelli, e-mail adrsc@dtu.dk . You can
-
benefits and a structured PhD training program About the research group You will join the Biomimetics, Biocarriers and Bioimplants group (The 3Bs), led by Associate Professor Leticia Hosta-Rigau at DTU
-
learning approaches and develop a theoretical understanding potentially based on differential geometry. In particular, deep neural networks perform surprisingly well on unseen data, a phenomenon known as