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#open_position -> closed

We are seeking 2–3 interns/collaborators:
- 2 positions focused primarily on technical aspects 
- 1 position with a 50/50 focus on theoretical and applied Machine Learning 

If you are interested in research on Histopathology Whole Slide Images (WSIs), VLMs, vLLMs, Self-Supervised Learning (SSL), and/or Theoretical Machine Learning—with the goal of submitting papers to conferences such as NeurIPS, ICLR, CVPR, ICASSP, WACV, or journals like IEEE Transactions on Medical Imaging, TMLR, and JMLR—please send your CV to [email protected]

For more context, you can review these relevant papers:
1. https://arxiv.org/abs/2408.08258
2. https://arxiv.org/abs/2306.11207
3. https://ieeexplore.ieee.org/document/10643565


Technical Requirements
- English proficiency at least B2 (preferred) or B1 
- Familiarity with Machine Learning and PyTorch 
- Experience with Git
- Ability to run and interpret academic GitHub repositories 
- Clean coding practices
- Solid understanding of Mathematics; preferably very strong in Probability and Statistics, Stochastic Processes, Information Theory, Machine Learning Theory, and High-Dimensional Statistics [for the theory-focused candidate]

Non-Technical Requirements
- Persistent and “try-hard” attitude 
- Available on-call 
- Enthusiastic about learning new platforms 
- Willing to dedicate significant time 
- Extremely resilient, comfortable with frequent schedule changes, and unafraid of polite rejections [for the theory-focused candidate]

Benefits
- Supportive RIML environment 
- Opportunity to work closely with Dr. Rohban (mainly for the theory-focused position) 
- Possibility of a research-related recommendation letter from Dr. Rohban

Final Thing
Guys, I really mean everything stated above for the Non-Technical Requirements, if you don’t meet them, please do’t email.



tg-me.com/RIMLLab/175
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#open_position -> closed

We are seeking 2–3 interns/collaborators:
- 2 positions focused primarily on technical aspects 
- 1 position with a 50/50 focus on theoretical and applied Machine Learning 

If you are interested in research on Histopathology Whole Slide Images (WSIs), VLMs, vLLMs, Self-Supervised Learning (SSL), and/or Theoretical Machine Learning—with the goal of submitting papers to conferences such as NeurIPS, ICLR, CVPR, ICASSP, WACV, or journals like IEEE Transactions on Medical Imaging, TMLR, and JMLR—please send your CV to [email protected]

For more context, you can review these relevant papers:
1. https://arxiv.org/abs/2408.08258
2. https://arxiv.org/abs/2306.11207
3. https://ieeexplore.ieee.org/document/10643565


Technical Requirements
- English proficiency at least B2 (preferred) or B1 
- Familiarity with Machine Learning and PyTorch 
- Experience with Git
- Ability to run and interpret academic GitHub repositories 
- Clean coding practices
- Solid understanding of Mathematics; preferably very strong in Probability and Statistics, Stochastic Processes, Information Theory, Machine Learning Theory, and High-Dimensional Statistics [for the theory-focused candidate]

Non-Technical Requirements
- Persistent and “try-hard” attitude 
- Available on-call 
- Enthusiastic about learning new platforms 
- Willing to dedicate significant time 
- Extremely resilient, comfortable with frequent schedule changes, and unafraid of polite rejections [for the theory-focused candidate]

Benefits
- Supportive RIML environment 
- Opportunity to work closely with Dr. Rohban (mainly for the theory-focused position) 
- Possibility of a research-related recommendation letter from Dr. Rohban

Final Thing
Guys, I really mean everything stated above for the Non-Technical Requirements, if you don’t meet them, please do’t email.

BY RIML Lab


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