The Computer Science department, Bernoulli Institute for Mathematics, Computer Science, and Artificial Intelligence, Faculty of Science and Engineering, University of Groningen invites applications for a 2-year Postdoc in Brain-inspired Inhibition in Deep Learning for Image Analysis.
One of the main challenges in learning algorithms for vision applications is the determination of computational models that can generalize beyond the training distribution and that are robust to adversarial attacks. This will be the focus of the two-year postdoc position.
The selected candidate will be enrolled with the Information Systems group, at the University of Groningen, and will collaborate with ongoing PhD students on the above-mentioned topic. The ideal candidate must have a solid foundation in developing deep learning architectures for vision applications and a proven record of publishing high-quality papers.
Tasks
In this position the candidate will:
- investigate the embedding of brain-inspired inhibition components in various deep learning architectures for deep hashing (retrieval), classification, and segmentation problems
- develop and evaluate methodologies of inhibition-augmented deep architectures
- collaborate with the 4 ongoing PhD projects working on first-person vision, medical, forensic, and radio astronomy image analysis.
Salary
- a salary of € 2,960 gross per month in the first year, up to a maximum of € 4,670 gross per month
- a holiday allowance of 8% gross annual income and an 8.3% year-end bonus.
Job Requirements
The successful candidate should:
- have a keen interest in pursuing fundamental research in deep learning with a focus on brain-inspired methodologies
- have a PhD degree in computer science, artificial intelligence, or another relevant field
- possess good analytical skills and a positive attitude towards collaborating with PhD students.
- have proven experience in building deep learning architectures with Python for computer vision problems
- have a proven track record in publishing high-quality peer-reviewed papers
- excellent verbal and written communication skills in English and a positive attitude towards collaborating with PhD students.
Application Process
Interested applicants are welcome to submit a complete application including:
- letter of motivation
- CV (including contact information for at least two academic references)
- transcripts from their bachelor’s and master’s degree
- certificate of the PhD degree.
To apply, click here.
Application Deadline: September 30, 2022.
For more information, visit the official site.
