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Job Id JOB ID-12583 Location Toulouse, France Date posted 06/18/2025 Category Enabling Functions
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This is a two-month internship created for a short collaborative project between In Silico R&D and BIX Toulouse, focused on applying cutting-edge machine-learning methods for early drug discovery. The intern, Chloë Bateman, has her internship agreement already signed by all parties, including the university and Evotec HR Toulouse. The signed internship agreement specifies the dates (16/06-14/08 2025) and the conditions of the internship.

Description of the subject:

Title: Application of advanced methods of machine learning in industrial drug discovery

Abstract: The goal of this internship is to explore the potential of recently developed tabular foundation models, TabPFN and TabICL, for tasks relevant to early-stage drug discovery, particularly in the fields of computational chemistry and computational biology.

Planned Tasks:

1) Conduct a comprehensive review of existing applications of tabular foundation models in the biomedical domain.
2) Identify relevant early drug discovery tasks where the use of tabular foundation models is justified and develop a computational workflow incorporating these models using available datasets.
3) Benchmark the performance of tabular foundation models against state-of-the-art machine learning approaches on the selected tasks.

FR : Dans le cadre de sa politique Diversité, Evotec étudie, à compétences égales, toutes les candidatures dont celles des personnes en situation de handicap.

ENG : In the frame of our Diversity policy, Evotec considers, with equal competences, all applications including people with disabilities.

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