Postdoctoral Researcher: Interpretable Classifier for Rare Classes in Marine Ecosystems
il y a 2 semaines
Job Opportunity: Postdoctoral Researcher in Interpretable Machine Learning
The INRIA team is seeking a highly skilled postdoctoral researcher to work on a project focused on developing interpretable classifiers for rare classes in marine ecosystems. The successful candidate will have a strong background in machine learning and experience with PyTorch/TensorFlow.
Project Overview
The project aims to extend existing XAI approaches to semi-supervised learning and rare domains, where multi-modal embeddings and LLM resources are less effective. The researcher will work closely with the INRIA team and other OceanIA teams to leverage domain knowledge and ground relevant sub-concepts in the classifier latent space.
Key Responsibilities
- Define a manageable corpus and develop a dictionary of relevant sub-concepts based on plankton ontologies and hierarchical classifications.
- Collaborate with researchers from other OceanIA teams and co-develop software/functionalities with INRIA project teams.
- Participate in the production of scientific articles and reports.
Requirements
- Good knowledge of machine learning and experience with PyTorch/TensorFlow.
- Flair for programming and teamwork.
Benefits
- Subsidized meals and partial reimbursement of public transport costs.
- Leave: 7 weeks of annual leave + 10 extra days off due to RTT + possibility of exceptional leave.
- Possibility of teleworking and flexible organization of working hours.
- Professional equipment available.
- Access to vocational training and social security coverage.
Salary
2788 € gross/month
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Orsay, Île-de-France INRIA Temps pleinJob OpportunityWe are seeking a highly motivated postdoctoral researcher to join our team at INRIA and contribute to the development of interpretable machine learning models for marine ecosystem identification. The successful candidate will work on extending existing XAI approaches to semi-supervised learning and rare domains, leveraging multimodal...
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