86 machine-learning "Fraunhofer Gesellschaft" positions

Master thesis: Advanced AI for time series prediction in automotive safety

The Fraunhofer-Gesellschaft (www.fraunhofer.de) currently operates 76 institutes and research facilities in Germany and is the world's leading organization for application-oriented research. Around

Student assistant performing OpenFOAM CFD simulations in the field of urban microclimate modeling

The Fraunhofer-Gesellschaft (www.fraunhofer.com) currently operates 76 institutes and research institutions throughout Germany and is the world’s leading applied research organization. Around 30 000

Thesis - Enhancing Machine Learning Transparency through Data Attribution

machine learning and common frameworks such as TensorFlow, PyTorch, or scikit-learn is a plus Knowledge of German is a plus What you can expect Opportunity to work at the intersection of research and

Thesis - Generating a Tree-Based Explanation for AI Models

clean and well-structured code Prior experience with machine learning and common frameworks such as TensorFlow, PyTorch, or scikit-learn is a plus Knowledge of German is a plus What you can expect

Exploring Machine Learning Applications in Real-Time Dose Verification for Proton Therapy

existing technologies, right through to the tested prototype. The Data-based Methods team at Fraunhofer ENAS develops real-world applications using AI, machine learning and computer vision. The main focus is

Master Thesis in Quantum Machine Learning

machine learning, we e.g. research how we could improve classical medical imaging procedures by quantum-assisted methods. This includes quantum Bayesian neural networks, which have a potential to allow for

Advanced Programmability of Heterogeneous Compute Platforms

existing technologies, right through to the tested prototype. The Data-based Methods team at Fraunhofer ENAS develops real-world applications using AI, machine learning and computer vision. The main focus is

Student assistant: »Physics-based machine learning for process optimization in machining domain«

The »High Performance Cutting« department develops technologies and application-oriented solutions for machining along the entire process chain - from process design to real-time data acquisition

Student assistant for the development of coupled multidomain physical models for hybrid EV systems

of the Modelica language is of great advantage experience and knowledge in numerical simulation techniques and multidomain coupled systems knowledge in machine learning and statistics is an added benefit good

Master Thesis in Quantum Error Mitigation

will research the utilization of current error mitigation methods. Thereby, the applications of quantum computing that this group is working on is diverse, ranging from various machine learning methods