Amgen Scholars: Announcements of Opportunity
Below are Announcements of Opportunity posted by Caltech faculty for the Amgen Scholars program.
Announcements of Opportunity are posted as they are received. Please check back regularly for new AO submissions! Remember: This is just one way that you can go about identifying a suitable project and/or mentor. For additional tips on identifying a mentor click here.
Please remember:
- Students pursuing Amgen must be U.S. citizens, U.S. permanent residents, or students with DACA status.
- Students pursuing Amgen must complete the 10-week program from June 18 - August 23, 2024. Students must commit to these dates. No exceptions will be made.
- Accepted students must live in provided Caltech housing.
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Project: | Testing feasibility of ML methods on various gene studies | ||||||||
Disciplines: | Data Science, Genomics | ||||||||
Mentor: |
Ashish Mahabal,
Deputy Director, Center for Data Driven Discovery, (PMA),
aam@astro.caltech.edu, |
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Mentor URL: | http://www.astro.caltech.edu/~aam (opens in new window) | ||||||||
Background: | We are exploring data science methods to investigate the efficacy of different methods on a set of inter-lab studies involving flow cytometry data, microbial strain collection data, cell-line provenance, genome editing inter-lab studies, viral vector reference material etc. The original aims of these studies did not include machine learning, and they often do not have huge data volumes to do purely data-driven studies. Yet, the data are amenable to the use of machine learning. | ||||||||
Description: | The project will involve picking up one or two of the sub areas mentioned above (not all!) and testing the feasibility of ML methods, and if/how scalability will improve results. | ||||||||
References: |
Flow cytometry: https://en.wikipedia.org/wiki/Flow_cytometry Viral vectors: https://en.wikipedia.org/wiki/Viral_vector Microbial strains: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4241729/ Cell line provenance: https://pubmed.ncbi.nlm.nih.gov/19003293/ Genome editing: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5131771/ |
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Student Requirements: | Proficiency in python, jupyter notebooks (Google Colab), and git. Conversant with basics of machine learning and statistics, knowledge about linux/unix. Basic biology knowledge and interest in genetics will be a plus. Knowledge about deep learning, GPUs, AWS will also be a bonus. Knowledge of R/Shiny will be a plus. | ||||||||
Programs: |
This AO can be done under the following programs:
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