176 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"University-of-Deusto" positions at ETH Zurich
Sort by
Refine Your Search
-
, including data management and the maintenance of computational infrastructure and software. Project background The position is part of the Institute of Microbiology at ETH Zurich and closely linked
-
We look forward to receiving your online application including a: CV publication list statement of research interests and the names and contact information of at least two references. Please note
-
therapies. Project background We are seeking a highly motivated Bioinformatics Scientist / Data Scientist to conduct multi-omics data analysis. This individual will play a key role in analyzing high
-
Balance (TV/TB) and hardware verification tests Develop and maintain thermal models of spaceborne platforms or thermal control technologies, correlating with test data for validation Establish thermal
-
. Isabel Z. Martínez and is based on rich administrative and survey data from Switzerland. The position offers the opportunity to gain insight into rigorous empirical research and to contribute actively
-
for open-ended arrangement. Workplace: ETH Zurich, with close interaction across departments and partner institutions worldwide. Further information about Professorship for International Relations and Data
-
. Project background Misinformation has severe negative effects on personal decision-making and societal integrity. In today’s information environment, misinformation is rampant. Over the past years
-
on our work and constantly improve it. We believe that the world can be improved with open data. Project background As part of our Open Science team, you will support us in developing efficient data
-
60%-80%, Zurich, fixed-term Are you an ambitious data scientist with strong analytical and numerical skills, and expertise in geomatics, remote sensing, and data processing? We invite you to join
-
these effects both require very high resolution and long time series of data, making it computationally expensive. By leveraging findings from recent km-scale modeling and exploiting high-resolution idealized