Expires on: 05/31/2024
The Martin Zhang Group at Carnegie Mellon University seeks a highly skilled Postdoctoral Researcher in Computational Biology to spearhead the development of innovative computational methods in statistical genetics. The successful candidate will play a pivotal role in advancing our understanding of heritable diseases and complex traits through computational analysis.
The selected candidate will lead the development of novel computational methods with significant biological implications. The research primarily focuses on mapping genes and cellular contexts for heritable diseases and complex traits. Additionally, the candidate will engage in the application of deep learning techniques for the integrated analysis of multimodal genetics and genomics data. Key research interests include disease-relevant cellular contexts and genes, expression quantitative trait loci (eQTLs), single-cell genomics, and the genetic architecture of diseases and complex traits. The Zhang Lab has a strong publication record in prestigious journals such as Nature, Nature Genetics, and conferences including NeuRIPS, ICML, and RECOMB.
Eligibility
- PhD degree in Computer Science, Computational Biology, Electrical Engineering, Genetics, or related quantitative fields.
- Strong publication record demonstrating original method development in statistical genetics or computational biology.
- Experience in analyzing genetics data, such as GWAS, and/or single-cell genomics data is advantageous but not mandatory.