Sort by
Refine Your Search
-
Category
-
Country
-
Field
-
candidate eager to operate at the interface of molecular biology, neuroscience, and AI. Responsibilities Wet-Lab & Experimental Work Set up and optimize imaging based spatial transcriptomics protocols.Set up
-
, technical, business and economic aspects related to the use of space resources for human and robotic exploration, as well as for a future in-space economy. You’d like to contribute to our mission? Join us
-
Job description: At the University of Vienna almost 11,000 personalities work together towards answering the big questions of the future. Around 7,700 of them do research and teaching, around 3,000
-
Do you want to contribute to the future sustainable use of forests? Apply to join the WIFORCE Research School at the University of Agricultural Sciences (SLU) in Sweden! The recruited PhD students
-
role Conduct research on data quality and long-term reliability in smart sensor systems for industrial monitoring Develop methods, models, and computational tools for sensor data validation, anomaly
-
conventional approaches with greener solutions adapt microelectronics processes to REC² materials, functionalities, and applications, and evaluate and optimize them for sustainability research direct fabrication
-
, through the rational design and optimization of microalgae-bacteria consortia, metabolic pathway regulation, nutrient partitioning, and bioreactor performance. You will become part of an international
-
- and nanofabrication and/or thin film deposition/analysis is beneficial but not a strict requirement. Your role in the TrueTime project You will investigate PCD, SiC and Si resonators through optimized
-
management Background: materials science, mechanical engineering, or a closely related discipline Apply: https://mgician.eu/research/doctoral-candidate-projects/dc6/ DC7: High-Performance Magnesium-Based
-
role Optimize monitoring strategies for predicting climate-driven slope risksShift from expert-driven, semi-random sensor placement to model-based Optimal Experimental Design Improve parameter