Doktorand inom generativ modellering för dataeffektiv maskininlärning
Core
Developing methods to reduce data volume without significantly impacting model performance for efficient optimization, while addressing fairness and privacy aspects in sensitive applications like medical diagnostics.
Role type
PhD researcher in generative modeling and data-efficient machine learning
Builds
Production ML models and synthetic representative data points
Domain
Artificial Intelligence, Machine Learning, Medical Imaging
Deliverable
production ML models
Required skills
Deep learning, Generative modeling, Data efficiency, Fairness in AI, Privacy (differential privacy), Python, LaTeX, Git, Linux
Preferred skills
Strong mathematical background, Implementation of new models/algorithms, Empirical testing of ML algorithms
Technologies
Python, GNU/Linux, Git, LaTeX
Responsibilities
Explore generative modeling to create synthetic data points, work with various dataset types (low/high-dimensional), implement and test ML algorithms empirically, conduct theoretical research
Seniority
PhD Candidate, Researcher
