Sort by
Refine Your Search
-
(UTC) Type of Contract Temporary Job Status Not Applicable Is the job funded through the EU Research Framework Programme? Not funded by an EU programme Is the Job related to staff position within a
-
Employment 0.8 - 1.0 FTE Gross monthly salary € 2,770 - € 3,539 Required background Research University Degree Organizational unit Faculty of Science Application deadline 30 April 2024 Apply now Are
-
now The Donders Centre for Cognition is looking for a PhD candidate in Computational Cognitive Science to work on a meta-theoretical research project spanning cognitive science and artificial
-
equivalent) in Psychology, Computer Science, Neuroscience, Physics, Math, or another related field. You must comply with the Marie Curie Actions mobility rule: the researcher must not have resided or carried
-
focuses on integration of the developed technology into a sensor. For the success of the programme, a close collaboration between the two projects and with the other project partners is crucial. Besides the
-
field, e.g. library science or data science, or will obtain this degree shortly. You have affinity with either computational text and network analysis methods (PhD 1) or qualitative social science methods
-
, philosophy of science, or a related field, e.g. library science or data science, or will obtain this degree shortly. You have affinity with either computational text and network analysis methods (PhD 1
-
you an aspiring computer science researcher interested in what can be done to make our digital world more secure? Then you have a part to play as a PhD candidate. By investigating techniques to design
-
(UTC) Type of Contract Temporary Job Status Not Applicable Is the job funded through the EU Research Framework Programme? Not funded by an EU programme Is the Job related to staff position within a
-
on complex problems. You hold a Master’s degree in Artificial Intelligence, Machine Learning, Computer Science or Computational Neuroscience. You have a strong foundation in developing machine learning