Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
- Computer Science
- Medical Sciences
- Biology
- Economics
- Chemistry
- Mathematics
- Science
- Engineering
- Linguistics
- Materials Science
- Psychology
- Environment
- Earth Sciences
- Electrical Engineering
- Arts and Literature
- Sports and Recreation
- Business
- Humanities
- Law
- Philosophy
- Social Sciences
- Education
- 12 more »
- « less
-
Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living
-
Data Science in the Faculty of Health, Medicine and Life Science at Swansea University, in addition to interacting with the research group in the Life Science department. The candidate will receive
-
, localization, and sensing, with a focus on developing next-generation multiple-antenna systems while optimizing overall system performance. As a doctoral student, you devote most of your time to doctoral studies
-
collaborative project that spans multiple continents. You will contribute to the development of new chronobiological analytics on existing data, design experiments to collect novel chronobiological data, engage
-
-Disciplinary Collaboration: Immerse yourself in a highly collaborative and interdisciplinary research environment, where you'll work alongside experts from fields such as engineering, data science, urban studies
-
environment, where you'll work alongside experts from fields such as engineering, data science, urban studies, and aerospace. Skill Development: Our extensive qualification concept goes beyond research
-
Temple University, CST Biology Position ID: Temple -BIOLOGY -RAP [#30052] Position Title: Position Location: Philadelphia, Pennsylvania 19122, United States of America [map ] Subject Area: Biology
-
learning (ML) for high-fidelity data ‘stitching’. The integration of data from multiple analytical platforms is critical for advancing the understanding of complex biological and chemical systems. This work
-
, leveraging existing literature and data from controlled experiments. The model will consider multiple photosynthesis parameters to predict microalgae growth. It will offer specific design criteria and
-
, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks Requirements: excellent university degree (master or comparable) in computer engineering or electrical