Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- AALTO UNIVERSITY
- ETH Zürich
- Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial
- RMIT University
- University of Florida
- CNRS
- Chalmers University of Technology
- Duke University
- European Commission - Joint Research Centre
- George Mason University
- Lucian Blaga University of Sibiu
- Luxembourg Institute of Science and Technology
- Luxembourg Institute of Science and Technology (LIST)
- NOVA.id.FCT- Associação para a Inovação de Desenvolvimento da FCT
- Northeastern University
- Purdue University
- Technical University of Denmark (DTU)
- The University of Chicago
- Tilburg University
- UNIVERSITAT POMPEU FABRA
- University of Arkansas
- University of Cambridge;
- University of Luxembourg
- University of Sheffield
- University of South Carolina
- University of South-Eastern Norway
- University of Texas Rio Grande Valley
- Vrije Universiteit Amsterdam (VU)
- Wageningen University & Research
- 19 more »
- « less
-
Field
-
modelling, machine learning, or microfluidics. They will also have excellent communication, organisational and problem-solving skills, and a strong interest in interdisciplinary quantitative biology
-
experience or strong interest in power system modeling, optimization, machine learning, and control systems. Documented programming experience (e.g., GitHub projects) in Python, Julia, MATLAB, or similar
-
companies. Hybrid & Data-Driven Modeling: Apply machine learning and hybrid physics-AI approaches to model industrial systems, accounting for physical constraints, sensor noise, and heterogeneous datasets
-
nutrition, such as: analysis of time series data and dynamic processes, where signals and responses evolve over time. statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and
-
Python programming. ● Experience in monitoring code performance. ● 3 or more years of demonstrable experience in machine learning theory. ● Excellent communication and teamwork skills. ● Proficiency in
-
field. Strong foundations in machine learning and familiarity with current AI tools and practices. A solid understanding of large language models, in particular their reliability, security, and
-
computational fluid dynamics. • Experience in modeling, uncertainty quantification, or statistical methods. • Experience in data science or machine learning is considered an asset. • Experience with high
-
). Desirable assets are: • Machine learning, deep-learning, artificial intelligence, advanced statistical inference; • A solid record of research activities, including relevant publications in international peer
-
for using AI to develop social engineering attempts. This project combines human subject research of learning and decision making, Human-Computer Interaction, and the advancement in AI methods
-
interactions between individual cells. Where to apply Website https://www.academictransfer.com/en/jobs/362788/post-doc-learning-interactions-… Requirements Specific Requirements PhD Degree in Physics Preferably