Internship - Prediction of probiotic potential from whole-genome sequences

Description du poste:

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The BioData department of the Lesaffre Institute of Science and Technology is seeking a highly motivated Intern to work at the interface of bacterial genomics and machine learning, and contribute to our ongoing projects in probiotic genome analysis. In this role, you will have the opportunity to apply state-of-the-art machine learning techniques to analyze bacterial genomic data and uncover novel insights about probiotic potential and functionality.
Key Responsibilities
* Collaborate with subject matter experts in microbiology and bioinformatics to understand the biological context and domain-specific challenges.
* Define and implement different strategies to extract genomic features frow whole genome sequences.
* Benchmark different machine learning approaches to build accurate and explainable predictive models.
* Build a comprehensive and documented software package to ensure the tools developed can be leveraged by Lesaffre for future studies.

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Ce qui fait de vous le candidat idéal

* Pursuing a degree in Computer Science, Bioinformatics, Computational Biology, or a related field.
* Strong background in machine learning, deep learning, and data analysis techniques.
* Proficiency in data-science languages like Python and R, and experience with popular machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn).
* Familiarity with biological sequence data formats, genomic databases, and bioinformatics tools.
* Good programming and development skills (Unix / bash, Git).
* Strong problem-solving, analytical, and critical thinking skills.
* Excellent communication and interpersonal skills.
* Curiosity and team spirit.
* Fluency in English.

The position is open for a duration of 6 months starting from January 2025.

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Tous nos postes sont ouverts aux personnes en situation de handicap.
All our positions are open to persons with disabilities