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Position: Postdoctoral Research Fellow in Bioinformatics/Computational Biology
Institution: Dana-Farber Cancer Institute
Location: Boston, Massachusetts, United States
Duties: Dr. Heng Li’s research group at Dana-Farber Cancer Institute (DFCI) and Harvard Medical School invites applicants for a bioinformatics/computation biology postdoctoral position. The general research theme is to tackle biological problems with advanced computational and statistical methods. The laboratory developed algorithms fundamental to the application of high-throughput sequence data, including sequence alignment (e.g. bwa and minimap2), sequence assembly (e.g. fermi, miniasm and wtdbg2), variant calling (e.g. samtools) and data query (e.g. tabix and bgt). The laboratory also studies species and human evolution (Mallick et al, Nature 2016 on SGDP), and analyzes single-cell sequencing data to investigate mutagenesis (e.g. Chen et al, Science 2017 on the LIANTI protocol), the 3D conformation of genomes (Tan et al, Science 2018 on dip-C) and the mosaicism between cells
Requirements: A PhD in a quantitative field such as bioinformatics, computational biology, computer science, mathematics, physics or a related discipline; Strong programming skills. Demonstrated experience in developing high-performance algorithms is beneficial; Familiarity with analysis of large-scale genomic sequence data; A strong track record of scientific publications; Good oral and written communication skills in English
   
Text: Postdoctoral Research Fellow in Bioinformatics/Computational Biology Dr. Heng Li’s research group at Dana-Farber Cancer Institute (DFCI) and Harvard Medical School invites applicants for a bioinformatics/computation biology postdoctoral position. The general research theme is to tackle biological problems with advanced computational and statistical methods. The laboratory developed algorithms fundamental to the application of high-throughput sequence data, including sequence alignment (e.g. bwa and minimap2), sequence assembly (e.g. fermi, miniasm and wtdbg2), variant calling (e.g. samtools) and data query (e.g. tabix and bgt). The laboratory also studies species and human evolution (Mallick et al, Nature 2016 on SGDP), and analyzes single-cell sequencing data to investigate mutagenesis (e.g. Chen et al, Science 2017 on the LIANTI protocol), the 3D conformation of genomes (Tan et al, Science 2018 on dip-C) and the mosaicism between cells A PhD in a quantitative field such as bioinformatics, computational biology, computer science, mathematics, physics or a related discipline; Strong programming skills. Demonstrated experience in developing high-performance algorithms is beneficial; Familiarity with analysis of large-scale genomic sequence data; A strong track record of scientific publications; Good oral and written communication skills in English
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