418 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"L2CM" positions in Denmark
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
perspective. Moreover, there will be an assessment of the applicant’s ability to perform research and teaching management tasks. Further information on the appointment procedure can be found in the Ministerial
-
Job Description The Centre for Machine Learning within the Data Science and Statistics Section of the Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark
-
for working within an interdisciplinary research team Strong analytical skills and ability to work independently Ability to convert experimental data into useful functioning models Preferred qualifications but
-
international partners for research projects Regular administrative tasks such as data entry, data gathering, and testing interfaces. Assistant with planning and working events hosted by the department Who we
-
participants and schools, coordinating data collection and managing ethics procedures Conducting school visits to engage directly with children, observe their behaviour and preferences, and collaborate with
-
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
-
. Interdisciplinary collaboration is central to our culture. BCE maintains strong partnerships across Aarhus University, including with the Departments of Mechanical Engineering, Electrical and Computer Engineering
-
Job Description IBIS is seeking a technically skilled and strategically minded Principal Software Engineer to develop and lead for a scalable, web-based data and collaboration platform supporting
-
accompanying family . Additional information about working in Denmark can be found at Work in Denmark . Regarding research funding support The Danish funding landscape is rich and diverse with several public and
-
graph algorithms for optimization under physical constraints Applying graph mining and graph data management techniques Designing computational methods for waste heat reuse and green transition goals