Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Germany
- Sweden
- France
- Norway
- Portugal
- Singapore
- Spain
- Belgium
- Netherlands
- Denmark
- United Arab Emirates
- China
- Italy
- Australia
- Canada
- Luxembourg
- Switzerland
- Hong Kong
- Austria
- Finland
- Poland
- Czech
- Ireland
- Estonia
- Japan
- Cyprus
- India
- Latvia
- Brazil
- Morocco
- Romania
- Saudi Arabia
- Lithuania
- South Africa
- Andorra
- Bulgaria
- Greece
- Taiwan
- Israel
- Slovenia
- Armenia
- Barbados
- Europe
- Iceland
- Malta
- Mexico
- New Zealand
- Slovakia
- Vietnam
- 41 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Economics
- Engineering
- Biology
- Science
- Business
- Mathematics
- Education
- Psychology
- Materials Science
- Arts and Literature
- Chemistry
- Social Sciences
- Humanities
- Linguistics
- Earth Sciences
- Environment
- Sports and Recreation
- Law
- Electrical Engineering
- Physics
- Design
- Philosophy
- 14 more »
- « less
-
/10.1016/j.xcrp.2022.101112 and https://doi.org/10.1080/08940886.2022.2114716 key words synchrotron radiation; X-ray Absorption Spectroscopy, machine learning, artificial analysis, autonomous experimentation
-
strengths of the University of Tübingen in Computer Sciences and Machine Learning. Potential research directions include, but are not limited to, phylogenetic, demographic, ecological and biogeographic
-
modeling, machine learning, or data-driven prediction methods applied to environmental datasets. Experience building and maintaining large, frequently updated archives of weather or climate observations
-
. Experience with Python programming. Familiarity with machine learning methods. Strong communication skills and ability to work collaboratively across theory and experiment. Desired Qualifications PhD in
-
, scalability, and effective performance across university use cases. Develops, trains, and fine-tunes machine learning models for a variety of university applications. Conducts experiments to evaluate model
-
cleaning and quality control, supervised and unsupervised machine learning, parametric and nonparametric statistical methods, deploying production models, and assisting with the communication of scientific
-
, and machine learning methods. Using regression analysis and vector autoregression (VAR) models, the study examines the relationship between macroeconomic variables and the performance of various
-
, numpy, scanpy, Squidpy, matplotlib, and others for single-cell and spatial analysis Interest in kidney research Exposure to machine learning and deep learning concepts Demonstrated ability to participate
-
understanding of all models of monitors and ECG machines utilized, be able to perform configuration on any specific monitor, replace defective equipment, report any equipment malfunctions to initiate repair, and
-
insurance, generous paid leave and retirement programs. To learn more about USC benefits, access the "Working at USC" section on the Applicant Portal at https://uscjobs.sc.edu. Research Grant or Time-limited