Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- Singapore
- United Kingdom
- Australia
- Germany
- Austria
- France
- Netherlands
- Spain
- Norway
- Sweden
- Belgium
- Portugal
- Denmark
- Canada
- United Arab Emirates
- China
- Italy
- India
- Switzerland
- Czech
- Ireland
- Luxembourg
- Poland
- Hong Kong
- New Zealand
- Romania
- Finland
- Japan
- Lithuania
- Morocco
- Saudi Arabia
- South Africa
- Cyprus
- Slovenia
- Andorra
- Armenia
- Barbados
- Brazil
- Croatia
- Estonia
- Europe
- Fiji
- Greece
- Kyrgyzstan
- Latvia
- Taiwan
- 37 more »
- « less
-
Program
-
Field
- Computer Science
- Economics
- Medical Sciences
- Science
- Business
- Engineering
- Biology
- Education
- Mathematics
- Arts and Literature
- Law
- Materials Science
- Humanities
- Social Sciences
- Chemistry
- Environment
- Linguistics
- Sports and Recreation
- Earth Sciences
- Psychology
- Philosophy
- Design
- Electrical Engineering
- Physics
- Statistics
- 15 more »
- « less
-
techniques such as yeast display and deep mutational scanning, or computational candidates with experience in generative AI, reinforcement learning, or agentic AI. The lab is supported by world-class
-
multidisciplinary team specializing in medical imaging and algorithm development. Our work focuses on advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities
-
computing subjects, including artificial intelligence. In addition, you will be able to demonstrate specialist expertise in one or more of the following areas: - Machine learning and deep learning
-
Mathematics, or a related field A strong background in image/signal processing, particularly in computer vision. Strong programming skills and experience with at least one deep learning framework e.g
-
, KELIM score), mutational profiles, histopathological information, and long-term survival outcomes. The first objective is to implement automated deep-learning–based segmentation of primary ovarian tumors
-
) for science with Dr. Aleksandra Ciprijanovic (alexciprijanovic.com) and her research group! The successful candidate will join a multidisciplinary team working at the intersection of deep learning, cosmology
-
data and models (mainly imaging data), with particular emphasis on fairness and privacy. Duties and responsibilities may change over time. The successful candidate will be part of the Deep Data Mining
-
programming, Bayesian deep learning, causal inference, reinforcement learning, graph neural networks, and geometric deep learning. In particular, you will be part of the Causality team under the supervision
-
an annual budget of 17 MCHF and about 170 researchers and collaborators, Idiap is today a key Swiss research institute in multiple AI fields, including machine learning (including deep learning, foundation
-
, or interaction for robotic systems Deep learning or applied machine learning for robotics Practical experience with robotic hardware, software development (e.g., Python, ROS, PyTorch, TensorFlow), and AI-based