Takeda is looking to solve drug discovery and development questions in Gastrointestinal & Inflammation Therapeutic Area by integrating and analyzing large screening datasets and metadata information using machine learning/deep learning based methods
Requirements
- Familiar with machine/deep- learning frameworks/libraries
- Experience in testing and implement different deep learning architecture is preferred
- Strong programming skills in R/Python
- Proficiency in Unix/Linux shell, AWS/HPC environment is preferred
- Working knowledge in molecular biology and clinical metadata
Responsibilities
- Leverage proprietary clinical multi-omics data assets and implement advanced AI/ML approaches
- Explore and experiment with innovative strategies for data integration, visualization, and analytical approaches
- Engage in the exploration of cutting-edge methodologies aimed at enhancing the precision and depth of analyses
- Contribute to the development of advanced techniques within the field of Precision Medicine and Biomarker Discovery
- Implement and test machine learning/deep learning based methods
- Integrate and analyze large screening datasets and metadata information
- Generate actionable insights and interpretation for drug discovery and development questions
Other
- Must be pursuing a Doctoral Degree in Computational Biology, Bioinformatics, Biostatistics and any other relevant fields
- Must be authorized to work in the U.S. on a permanent basis without requiring sponsorship
- Must be currently enrolled in a degree program graduating December 2026 or later
- Able to work full time 40 hours a week during internship dates
- Quick learner, Outstanding oral and written communication skills
