The University at Buffalo, Department of UB Genomics and Bioinformatics is seeking candidates for the position of Bioinformatics Analyst. The Bioinformatics Analyst is responsible for supporting the ever-growing computational analysis needs of the Genomics and Bioinformatics Core. The Bioinformatics Analyst works directly with core laboratory staff in an effort to provide optimal next-generation sequencing results.
Specific responsibilities include:
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- Day-to-day processing of the immense data being generated from illumina based next-generation sequencing platforms;
- Quality assurance, initial data processing, and storage of data generated;
- Maintenance of core computational infrastructure;
- Specialized downstream analysis for supporting projects and core initiatives;
- Willingness to quickly adopt new technologies and analysis best practices;
- Analysis of all types of genomic, epigenomic, and transcriptomic data generated by the core
- Development and modification of computational algorithms to facilitate data analysis at UB; participating in manuscripts and grant applications,
- Figure generation;
- Custom data mining efforts.
As an Equal Opportunity / Affirmative Action employer, the Research Foundation will not discriminate in its employment practices due to an applicant’s race, color, religion, sex, sexual orientation, gender identity, national origin and veteran or disability status.
Minimum Qualifications:
The ideal candidate will be collaborative, self-directed and possess the following:
- A bachelors degree in Bioinformatics or closely related field with 1-2 years experience and familiarity with common NGS data file formats (FastQ, BAM). Education and experience equivalencies will be considered.
- Knowledge of Illumina based sequencing platforms (NovaSeq, NextSeq500, MiSeq).
- Proficiency in linux is essential as all workflows are in a linux cluster environment.
- Proficiency in the R coding language with experience using RStudio and Bioconductor.
- Hands on experience processing Next-Generation Sequencing data sets from raw data to alignment (Bowtie2/Hisat2 preferred), and quantification (Subread featureCounts).
- Previous experience using the DESeq2 analysis package from RNA-Seq.
- Background knowledge of wet bench techniques to aid in laboratory trouble shooting.
- Outstanding communication and leadership skills, in interacting with both wet-lab and computational biologists.
Preferred Qualifications:
- A Masters degree in Bioinformatics or closely related field.
- Experience in transcriptional analysis is strongly preferred.
- Python coding skills strongly preferred (virtualenv, managing local packages).
- Previous hands-on experience with wet bench assays a plus, but not required.
