UNIV - Post Doctoral Fellow - Department of Biochemistry

Job Description Summary

Job Summary:
The laboratory of Dr. Sahin in the Department of Biochemistry and Molecular Biology at MUSC is currently recruiting a talented & motivated post-doctoral fellow in the field of bioinformatics with cancer biology. Qualified candidates should have training in bioinformatics analyses to support the expanding emphasis on projects focused on elucidating the relationship of treatment responses, particularly immunotherapy, and the genomic landscape of patient tumors. A doctoral degree is required in related areas: bioinformatics, genomics, genetics, computational biology, biomedical informatics, computer science, medicine, biostatistics, or related disciplines.
The Sahin lab focuses on elucidating the molecular mechanisms of cancer therapeutics, drug resistance, and metastasis mainly in breast and kidney cancers (Cell Death Dis, 2024. doi.org/10.1038/s41419-024-06814-3, Cancer Research, 2024, doi.org/10.1158/0008-5472.CAN-23-2812, Nature Communications, 2023, doi: 10.1038/s41467-023-42736-y, Cell Death & Differentiation, 2023, doi: 10.1038/s41418-023-01140-1). We are also interested in developing and pre-clinical testing of novel anti-cancer therapeutics that are easily translatable to clinics (Cell Chem. Biology, 2024, doi.org/10.1016/j.chembiol.2024.06.012). The major research theme of the Sahin lab is to identify the mechanisms of drug resistance/metastasis and target these resistance/metastasis-driving factors with either own developed compounds or available drugs to overcome resistance/block metastasis. Combining animal models with high-throughput transcriptomics/proteomics approaches, bioinformatics/modeling tools and clinical sample analyses, our dynamic group focuses on identifying novel targets overcoming resistance to state-of-art clinically approved or -tested drugs and preventing metastatic spread of breast cancer. Studies will use a range of complementary methods including biochemistry, molecular and cellular biology, single cell transcriptomics/proteomics, functional cell-based assays, and mouse genetic models. Our projects are funded by the grants from the National Institutes of Health, the American Cancer Society, The Department of Defense, Mary Kay Foundation and SmartState Program of South Carolina.

Entity

Medical University of South Carolina (MUSC - Univ)

Worker Type

Employee

Worker Sub-Type​

Regular

Cost Center

CC000954 COM BIOCHEM Operations CC

Pay Rate Type

Salary

Pay Grade

University-00

Pay Range

0.00 - 0.00 - 0.000

Scheduled Weekly Hours

40

Work Shift

Job Description

Job Summary: 

The laboratory of Dr. Sahin in the Department of Biochemistry and Molecular Biology at MUSC is currently recruiting a talented & motivated post-doctoral fellow in the field of bioinformatics with cancer biology. Qualified candidates should have training in bioinformatics analyses to support the expanding emphasis on projects focused on elucidating the relationship of treatment responses, particularly immunotherapy, and the genomic landscape of patient tumors. A doctoral degree is required in related areas: bioinformatics, genomics, genetics, computational biology, biomedical informatics, computer science, medicine, biostatistics, or related disciplines.

The Sahin lab focuses on elucidating the molecular mechanisms of cancer therapeutics, drug resistance, and metastasis mainly in breast and kidney cancers (Cell Death Dis, 2024. doi.org/10.1038/s41419-024-06814-3, Cancer Research, 2024, doi.org/10.1158/0008-5472.CAN-23-2812, Nature Communications, 2023, doi: 10.1038/s41467-023-42736-y, Cell Death & Differentiation, 2023, doi: 10.1038/s41418-023-01140-1). We are also interested in developing and pre-clinical testing of novel anti-cancer therapeutics that are easily translatable to clinics (Cell Chem. Biology, 2024, doi.org/10.1016/j.chembiol.2024.06.012). The major research theme of the Sahin lab is to identify the mechanisms of drug resistance/metastasis and target these resistance/metastasis-driving factors with either own developed compounds or available drugs to overcome resistance/block metastasis. Combining animal models with high-throughput transcriptomics/proteomics approaches, bioinformatics/modeling tools and clinical sample analyses, our dynamic group focuses on identifying novel targets overcoming resistance to state-of-art clinically approved or -tested drugs and preventing metastatic spread of breast cancer. Studies will use a range of complementary methods i