PhD Position on Statistical Theory: This scholarship offers a PhD position focusing on unraveling the theoretical foundations of deep learning-based image classification using statistical theory.
PhD Position on Statistical Theory for Deep Learning based Image Classification
- Designation: PhD Candidate
- Research Area: Statistical Theory for Deep Learning in Image Classification
- Location: University of Twente, Netherlands
- Eligibility/Qualification:
- Enthusiastic and highly motivated researcher
- Master’s degree in Mathematics, Statistics, or Theoretical Computer Science (or a related field)
- Preferably experience in mathematics of deep learning or machine learning theory
- Creative mindset, excellent analytical, and communication skills
- Team player, comfortable in an internationally oriented environment
- Fluency in English
- Job Description:
- Investigate theoretical properties of network architectures
- Assess how network depth influences performance
- Delve into the learning processes of Convolutional Neural Networks (CNNs)
- Applications to medical image data to connect theory with practice
- How to Apply:
- Applicants are invited to submit their applications via the ‘Apply now’ button on the vacancy webpage.
- For more information, contact Sophie Langer via s.langer@utwente.nl.
- Last Date for Apply:
- Application deadline: September 6, 2024
This PhD position offers a valuable opportunity to delve into the core principles of deep learning in image classification, bridging theory and application in a stimulating scientific environment at the University of Twente in the Netherlands. Apply now and be part of the cutting-edge research to advance the understanding of artificial intelligence and statistical theory in image processing.
