Postdoktor inom kvalitetsmedveten maskininlärning för ansvarsfull AI
Core
Developing quality-aware representation learning frameworks for responsible and sustainable machine learning systems that balance predictive performance with fairness, privacy, and sustainability goals.
Role type
Postdoctoral researcher (Quality-Aware Representation Learning)
Builds
New representation learning methods, benchmarks, and evaluation protocols for trustworthy AI
Domain
Artificial Intelligence / Machine Learning / Responsible AI
Deliverable
production ML models
Required skills
Independent research, publication in peer-reviewed venues, computational programming, data analysis
Preferred skills
Representation learning, trustworthy AI, large language models (LLMs), multi-objective optimization, synthetic data, cross-disciplinary research, open-source software, reproducible research methods, ethical/legal/policy perspectives on AI
Technologies
Python, PyTorch, TensorFlow, Hugging Face, Scikit-learn, Jupyter, Git, Docker, Kubernetes, AWS, GCP, Azure, Kubernetes, TensorFlow, PyTorch, Scikit-learn, Jupyter, Git, Docker, Kubernetes, AWS, GCP, Azure
Responsibilities
Develop and evaluate new methods for representation learning, create benchmarks and evaluation protocols, collaborate with interdisciplinary researchers and societal actors
Seniority
Postdoctoral researcher (early career after PhD)
