Senior Bioinformatics Research

Senior Bioinformatics Research

We are seeking a highly motivated post-doc trainee to join Dr. Norbert Perrimon's group in the Program of Genetics at Harvard Medical School. Perrimon lab is actively generating data sets of omics scale and this position will involve working with other post-doc trainees in the lab who are responsible of design and generating such datasets. In addition, this position involves working with DRSC/TRiP functional genomics core, a multi-disciplinary team of biologists, software engineers and bioinformaticians as we develop and leverage technological breakthroughs to explore the biology of complex systems. Principal Responsibilities include 1.) Design and implement reusable bioinformatics analysis pipelines for processing RNA-seq, single-cell RNA-seq, genomics and proteomics data. Develop novel algorithms and integrated data visualization applications when existing software packages are not available or are not adequate. 2.) Apply computational, statistical, and AI/ML approaches to uncover biological insights and support functional discovery by analyzing multi-omics datasets eg. genomics, transcriptomics, proteomics, metabolomics, and related datasets. 3.) Help develop custom databases, web portals and pipelines for managing raw and processed experimental data as well as reagent identification/designs. 4.) Collaborate closely with Investigator and lab members on research projects including defining the scope of the collaboration, researching the scientific topics and implementing the appropriate bioinformatics solutions that meet project timelines. Coordinate and collaborate with other bioinformaticians, biostatisticians, information technology professionals, and interdepartmental project teams. 5.) Properly document the procedures used in computational analysis, provide the summary reports of results, and contribute to grant and manuscript writing.

Basic Qualifications - Doctoral degree in Bioinformatics or in biology with extensive experience analyzing omics data. Strong background in programming, algorithms and statistics. Familiarity with programming techniques for analyzing data sets and experience working with BIGDATA (eg. NGS data in multi-TB scale). Experience using genome alignment software (bowtie2, bwa, tophat, etc.) is desired. Fluent in one programming language (Python, C, C++ or Java) and familiarity with scripting languages (bash, Perl). Knowledge of Unix operating system, terminal and bash is a plus. Experience using a compute cluster. Excellent information management skills.

Additional Qualifications - Experience using relational databases, SQL and / or structured data formats. Web programming experience (PHP, Django, JavaScript, JQuery, JSON, REST API) is a plus. Excellent oral and written communication skills as well as the ability to collaborate effectively with a diverse team.