Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
- Computer Science
- Medical Sciences
- Biology
- Science
- Engineering
- Mathematics
- Economics
- Chemistry
- Humanities
- Materials Science
- Earth Sciences
- Psychology
- Linguistics
- Arts and Literature
- Business
- Social Sciences
- Electrical Engineering
- Environment
- Sports and Recreation
- Education
- Law
- Physics
- 12 more »
- « less
-
analyses. The postdoc will be hosted at TDB, co-supervised by both groups, and will work at the interface of scientific computing, machine learning and particle physics. Project description Searches for dark
-
looking for a postdoctoral researcher in the area of Generative AI. VITA research interests lie at the intersection of Computer Vision, Machine Learning (Deep Learning), and Human-Robot Interaction
-
than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries. Postdoc in ML-Based Co-Design at EPFL Mission The EPFL computer vision lab (https://www.epfl.ch
-
Finance at EPFL seeks postdocs to reinforce our research in quantitative finance with a focus on applied machine learning. Main duties and responsibilities Working and collaborating on research projects
-
Offer Description KEYWORDS: bioinformatics, metagenomics, metabolomics, cancer, machine learning, artificial intelligence Principal Investigator
-
related to modeling and simulation of biological systems, 3) very good IT skills, in particular the ability to program in Python, 4) very good knowledge of machine learning methods, neural networks, and
-
/nanoplastics, and other environmental compounds to assess their potential impacts on human health and the environment using machine learning (ML), deep learning (DL), and big data analytics. His lab is
-
their added value against simpler machine-learning baselines; train and evaluate ARCA on large-scale microbiome datasets, with attention to sparsity, batch effects, scalability, generalisation across studies
-
Physics Informed Machine Learning method which exploits the advantages of physics-based and data-driven models, while mitigating the disadvantages. This research will contain experimental and modelling
-
(e.g., ROS, MoveIt) and hardware integration. Knowledge of machine learning, reinforcement learning, or vision-language models for robotics is a plus. Hands-on experience with robotic arms (e.g., UR5