Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Austria
- Germany
- France
- Netherlands
- Norway
- Australia
- Belgium
- Denmark
- Singapore
- Sweden
- Spain
- China
- Czech
- India
- Switzerland
- Luxembourg
- Portugal
- United Arab Emirates
- Canada
- Ireland
- Poland
- Hong Kong
- Italy
- Lithuania
- Romania
- Morocco
- New Zealand
- South Africa
- Andorra
- Armenia
- Barbados
- Croatia
- Cyprus
- Estonia
- Europe
- Finland
- Kyrgyzstan
- Latvia
- Slovenia
- 31 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Biology
- Engineering
- Science
- Economics
- Mathematics
- Business
- Environment
- Chemistry
- Humanities
- Linguistics
- Arts and Literature
- Education
- Law
- Social Sciences
- Earth Sciences
- Philosophy
- Materials Science
- Psychology
- Electrical Engineering
- Physics
- Sports and Recreation
- Design
- 14 more »
- « less
-
volume, revenue, and strategic partnerships in Bioengineering and therapeutic platforms, by combining deep faculty engagement, domain knowledge and market intelligence to cultivate, source, shape, and
-
emphasizes academic excellence, experiential learning, and meaningful engagement with local industry partners. We are seeking an individual who brings a strong research profile, deep industry experience, and a
-
structural biology, expanding the scope and impact of the project while providing valuable training and mentorship opportunities. For more information about the Clark Lab, please visit: https://the-clark
-
, Mechanical), Computer Science, Applied Math/Statistics, Physics—or related. Candidates who will graduate in the near future are also welcome to apply. Strong foundation in machine learning/deep learning and
-
proven track record in teaching excellence that creates deep and lasting impact on student learning and development; (f) outstanding contribution to programme development leading to substantial
-
members have been working on statistics learning, granular computing and knowledge discovery, machine learning, deep learning, and specifically interpretable artificial intelligence. Many innovative
-
closely related quantitative discipline. Demonstrated experience with large-scale deep learning models and modern ML frameworks (e.g., PyTorch, JAX, Transformers), including training, fine-tuning
-
analysis (FEA) and strong skills in FEA software such as ABAQUS Hands-on experience in the construction and application of deep learning neural networks on material design by using PyTorch or Matlab PLEASE
-
of Kentucky. The ideal candidate will have deep training, preferably a PhD or another terminal degree, in an academic discipline. All specializations are invited to apply. The appointment comes with
-
knowledge to real-world circumstances. Candidates must have a PhD, J.D. or other terminal degree in their academic discipline to be able to teach a graduate-level course. Candidates with an MA plus 20 years