Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
a citizen science component to gain a broader data foundation and raise awareness of the issue. The results will support management measures and policy initiatives to reduce plastic pollution
-
of the jobpost. Further information We recommend that you save a copy of the job posting, as it will be removed once the application deadline has passed. The assessment of candidates for the position will be
-
-disciplinary teams. The preferred candidate has a strong interest in advanced manufacturing of mechanical and electrical products and competencies in applying life cycle assessment (LCA) data to derive decision
-
achieve automated data driven optimization (in terms of time and quality) of polishing process parameters by application of machine learning algorithms, leading to a robust, repeatable and fast polishing
-
indicated research directions This description should outline the applicant’s thoughts and ideas within the overall aim of the S4OS project. CV. Diploma and transcripts of records. Other relevant information
-
paid fellowship with a very competitive salary (a minimum monthly gross salary of DKK 36,138 including pension) and excellent conditions to excel in their research. Further information is available
-
including pension) and excellent conditions to excel in their research. Further information is available Associate Professor Ramkrishan Maheshwari, phone: +45 65 50 16 86, email: ramkrishan@sdu.dk If you
-
interdisciplinary environment, which offers fantastic scientific and social interactions with a large group of talented researchers. Further information on the Niels Bohr Institute is found at https://nbi.ku.dk
-
synthetic fuel reactors. Tasks include gas handling, system diagnostics, thermal integration, and performance evaluation under variable power inputs. Data Analysis and Machine Learning: Collect and process
-
of Markets Globalization, Migration and Urbanization Growth, Unemployment, and Inflation Quantitative/Empirical Methods and Data Science Welfare: Education, Health Care and Pensions The Department of Economics