A Ph.D. student level summer intern position in computational biology (Global Computational Biology) within Takeda Boston that is tasked with supporting the efforts for target identification.
DUTIES & RESPONSIBILITIES
- Develop method utilizing deep learning or other machine learning framework to predict function of microbial proteome.
- Run literature search and method evaluation.
- Write reports and give presentations on the analysis results to internal/external audience.
- A PhD student in computational biology, bioinformatics, human genetics or statistical genetics, biostatistics, computer science, mathematics or relevant engineering fields.
- Strong quantitative science background including statistics, data mining, and machine learning, particularly deep learning algorithms.
- Strong knowledge on human genetics or statistical genetics.
- Good experiences with statistical modeling for associating genetic features with phenotypes such as treatment response or disease subtypes.
- Experiences with next-generation sequencing data analysis are appreciated.
- Sufficient programming exposure to R. Experiences with Python, Perl, Matlab, C/C++, or JAVA are also appreciated.
- Experience with tensorflow preferred.
- Excellent communication skills.
Paid Intern (Fixed Term) (Trainee)