Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Sweden
- Norway
- Germany
- France
- Netherlands
- Denmark
- Belgium
- Hong Kong
- Austria
- Poland
- Singapore
- Australia
- Spain
- Switzerland
- Estonia
- Portugal
- China
- Italy
- Luxembourg
- United Arab Emirates
- Canada
- Cyprus
- Czech
- Ireland
- Finland
- Morocco
- Saudi Arabia
- Barbados
- Brazil
- Europe
- Iceland
- India
- Japan
- Lithuania
- New Zealand
- Taiwan
- Worldwide
- 29 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Engineering
- Biology
- Science
- Economics
- Mathematics
- Psychology
- Humanities
- Materials Science
- Chemistry
- Linguistics
- Arts and Literature
- Education
- Environment
- Business
- Earth Sciences
- Electrical Engineering
- Physics
- Social Sciences
- Sports and Recreation
- Law
- 12 more »
- « less
-
with Machine Learning Highly motivated to learn about biology and (the study of) biological data Enthusiastic team player Desirable but not required Experience with single-cell omics data Experience with
-
analysis. • Hydrological and hydraulic simulation. • Machine learning, including unsupervised clustering and predictive modelling. • Working with large, complex, multi-source datasets using MATLAB, Python
-
(1–4) and in related projects. We encourage potential PhD candidates to visit our webpage to learn more about the research we are conducting. The PhD candidate is expected to be enrolled in two
-
, as well as other sustainability relevant endeavours Integrating advanced machine learning methods in thermodynamics for computer-aided property predictions, molecular and product design and
-
both independently and as part of an international, interdisciplinary team Assets•Experience with computer vision or deep learning (e.g. PyTorch, TensorFlow)•Familiarity with street view imagery or other
-
-based transfer learning classification model for two-class motor imagery brain-computer interface. International Journal of Neural Systems (IJNS). https://doi.org/10.1142/S0129065719500254 * Kudithipudi
-
, as well as other sustainability relevant endeavours Integrating advanced machine learning methods in thermodynamics for computer-aided property predictions, molecular and product design and
-
Skills Good interpersonal communication (oral and written) and organizational skills required Comfortable with modern computer operating systems, such as Mac OS or Windows, and strong foundation in basic
-
to machine learning algorithms in order to get uncertainty estimates for parameters governing the distribution of the observed data. The predictive Bayes scheme for uncertainty quantification contains a wide
-
learning. This PhD provides a unique opportunity to shape emerging concepts in Artificial Intelligence Informed Mechanics (AIIM), combining fundamental research with methodological innovation. You will gain