Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Netherlands
- Australia
- France
- Singapore
- Germany
- Belgium
- Norway
- Sweden
- Spain
- Austria
- Denmark
- Switzerland
- United Arab Emirates
- Portugal
- Canada
- India
- China
- Finland
- Italy
- South Africa
- Ireland
- Poland
- Brazil
- Czech
- Luxembourg
- Macau
- Cyprus
- Estonia
- Hong Kong
- New Zealand
- 22 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Engineering
- Economics
- Biology
- Science
- Business
- Mathematics
- Earth Sciences
- Chemistry
- Humanities
- Education
- Arts and Literature
- Materials Science
- Psychology
- Social Sciences
- Philosophy
- Environment
- Electrical Engineering
- Law
- Linguistics
- Sports and Recreation
- 12 more »
- « less
-
learning and deep learning applied to electroencephalography in the context of brain-computer interfaces, including experience with MATLAB and Python and in the design and conduct of experimental studies
-
network inference and modeling, machine learning and deep learning. Experience in working with Arabidopsis and plant genome data is a strong plus. The position is expected to continue for multiple years
-
/Qualifications Strong research track record in AI and scientific applications. Excellent knowledge of Machine Learning and Deep Learning. Strong Python programming skills. Experience with PyTorch, TensorFlow
-
field Strong background and expertise in data science, bioinformatics, network science, artificial intelligence, machine learning, deep learning, or related areas. Solid understanding of AI algorithms
-
with the mission of our university. To learn more about the mission, vision, and values of the College of Liberal Arts & Sciences, visit: https://las.illinois.edu . Successful candidates are expected
-
Learning. Experience with the deep learning ecosystem and high-performance computing infrastructures. Experience designing and conducting experiments with human participants is a strong plus. Experience in
-
Brandenburgische Technische Universität Cottbus | Cottbus, Brandenburg | Germany | about 2 months ago
candidate is expected to incorporate innovative approaches into their research that connect classical probabilistic models with modern deep learning architectures. Examples include Bayesian deep learning
-
(including numerical optimisation, variational methods and MCMC sampling) C3 State-of-the-art deep learning (including transformers, graph neural networks and normalising flows) C4 Use of GPU programming and
-
outstanding teaching in JD and postgraduate programmes, innovating curriculum in Equity and Trusts. Supervise and mentor PhD and higher degree students, nurturing the next generation of private law scholars
-
on healthcare data. - Experience in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL) particularly in Natural Language Processing (NLP) and Computer Vision (CV) - strong record