Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
satisfy the enrolment requirements for the PhD programme at the University of Bergen. We can offer: a good and professionally stimulating working environment including a comprehensive network of
-
professionally stimulating working environment including a comprehensive network of international collaborators. salary as PhD research fellow (code 1017) in the state salary scale. This constitutes a gross annual
-
. The fellowship period is 3 years. The project will provide a fundamental understanding of droplet flow on single and complex fiber networks. Essential to the project is the development of a new understanding of
-
, and collaborative international working environment that values diverse perspectives Access to a strong network of top-level national and international collaborators Research mobility funds supporting
-
towards this goal. The PhD research fellow will be part of the PhD programme in Computer Science: Software Engineering, Sensor Networks and Engineering Computing (https://www.hvl.no/en/research/phd
-
for Space Communications Research . The person hired will work within research on: Quantum information theory, Quantum compressive sensing, Quantum error-correcting codes, Quantum computing, and/or Post
-
The position is fully funded and based at NHM’s interdisciplinary and highly international research group Evolution, eDNA, Genomics and Ethnobotany (EDGE) . Opportunities for networking across evolutionary
-
colleagues Attractive welfare benefits in the State Pension Plan Opportunity for physical activities within working hours Salary PhD Research Fellow (code 1017): NOK 550 800 a year. Further promotion will be
-
realistic settings referring to statistical and system characteristics in the real world contrary to an ideal learing setting. The candidate will contribute to understanding how neural networks extract
-
to an ideal learing setting. The candidate will contribute to understanding how neural networks extract the most relevant information of the data to make a prediction using advanced mathematical tools