Jackelyn Golden, PhD
Post Doctoral ScholarDepartment of Population and Quantitative Health SciencesSchool of MedicineEmail: jxg406@case.edu
Michelle Grunin, PhD
Post-Doctoral FellowDepartment of Population & Quantitative Health SciencesSchool of MedicineEmail: mag235@case.edu
Eun Kyung Lee, PhD
Post Doctoral ScholarDepartment of Population and Quantitative Health SciencesSchool of MedicineDavid Ngendahimana, PhD
Post Doctoral ScholarDepartment of Population and Quantitative Health SciencesMary Ann Swetland Center for Environmental HealthSchool of MedicineEmail: dkn18@case.edu
Ellen Palmer, PhD
Post-Doctoral FellowDepartment of Population & Quantitative Health SciencesSchool of MedicineEmail: elp76@case.edu
Lindsay Noelani Sausville, PhD
Post Doctoral FellowDepartment of Population and Quantitative Health SciencesSchool of MedicineAndrea Waksmunski, PhD
Post Doctoral ScholarDepartment of Population and Quantitative Health SciencesSchool of MedicineEmail: axw360@case.edu
Owusua Yamoah, PhD
Post Doctoral ScholarDepartment of Population and Quantitative Health SciencesSchool of Medicine
Post Doctoral Position in Human Quantitative Genomics - Population and Quantitative Health Sciences
Posted January 11, 2021
Post Doctoral Position in Human Quantitative Genomics
Department of Population & Quantitative Health Sciences
Cleveland Institute for Computational Biology
Case Western Reserve University
We are seeking a highly motivated postdoctoral fellow to join our team at Case Western Reserve University in the laboratory of Dr. Jonathan Haines (http://haineslab.org/). The position is available immediately and will be focused on pursuing quantitative genomic studies with an emphasis on Alzheimer's disease and other neurological disorders. The successful candidate will have a Ph.D. degree (or equivalent) in genetics, genomics, epidemiology, computational biology, bioinformatics, biostatistics, computer science, or related field, and have experience and/or interest in computational, analytical, or statistical genomics research. Familiarity with the Unix/Linux environment and programming/scripting in Python and R is preferred.