Mentor Areas
Dr. Kamoun’s current interests are focused on understanding the significance of HLA amino acid polymorphisms in clinical transplantation using a multidisciplinary approach combining molecular techniques with bioinformatics and machine learning bin discovery methods.
Description:
Dr. Malek Kamoun is collaborating with Dr. Ryan Urbanowicz in applying machine-learning bin discovery methods that can automatically engineer features to better evaluate the risk of kidney transplant outcomes based on HLA immunogenetics data. Machine learning bin discovery and feature engineering tools are used to evaluate the associations of HLA amino acid polymorphisms with kidney transplant outcomes. Developing and applying smarter machine learning methods is critical to biomedical data mining and many other real-world applications.
Preferred Qualifications
- Experience with programming in Python (mastery of basics preferred, but commitment to learn welcome).
- Interest and/or experience in machine learning, data analysis, informatics, and/or statistics encouraged.
Project Website
Learn more about the researcher and/or the project here. https://researchers.cedars-sinai.edu/Ryan.Urbanowicz
Details:
Preferred Student Year
First-year, Second-Year, Junior, Senior
Academic Term
Fall, Spring, Summer
I prefer to have students start during the above term(s).Volunteer
Yes
Yes indicates that faculty are open to volunteers.Paid
Yes
Yes indicates that faculty are open to paying students they engage in their research, regardless of their work-study eligibility.Work Study
Yes
Yes indicates that faculty are open to hiring work-study-eligible students.