Computational Biology/Bio-informatics Post-Doctoral Researcher
Computational Biology/Bioinformatics Post-doctoral position available immediately
We are seeking a talented, highly motivated individual to join the laboratory headed by Professor David Sinclair in the Genetics Department at Harvard Medical School, Boston. The Sinclair lab is known for their work on genes and small molecules that delay aging and treat age-related diseases. The lab has a wide range or expertise and interests, including cancer, neurodegeneration, diabetes, and fertility. The laboratory has a record of innovation with over 30 patents and numerous start-up companies. In 2014, Dr. Sinclair was on the TIME100 list of the “most influential people in the world.”
The individual will take the lead in the analysis of “Big Data”, including genome sequence and, de novo assembly, RNA-seq, ChiP-seq, ribosome profiling and proteomics from new species ranging from microbes to mammals. This highly skilled individual will work within a multidisciplinary team to process and interpret experimental data. The individual will present regular updates to academic and industry collaborators as well as prepare and publish research reports. There is a real opportunity to invent and to innovate.
- Lead the development of new methods and algorithms to identify, characterize and monitor alterations in DNA, RNA and protein derived from experimental specimens.
- Implement new analytical tools capable of troubleshooting and accelerating the data analysis.
- Work with the molecular biology team to develop protocols that enable parallel interpretation of sequencing and proteomics data.
- Process, analyze and interpret high volumes of data as part of wide range of internal and external scientific studies. Apply automated methods and software to support large-scale bioinformatics analysis.
- Provide bioinformatics resources for day-to-day use by members of the laboratory.
- Monitor and evaluate analytical aspects of new and emerging technologies (sequencing proteomics and others).
- Present scientific and technical data to both internal and external scientific colleagues in a clear and cohesive manner.
- Work independently and prepare timetables, deliverables, and project schedules.
The ideal candidate will have a record of scientific rigor, creativity, and ability to work in teams, with a strong publication record in peer-reviewed scientific journals. Candidates should have a strong background in genomics, and preferably in proteomics and metabolomics. Excellent oral and written communication skills are required.
- Ph.D. in Bioinformatics, Computational Biology, Computer Science or related fields.
- Experience with and deep understanding of algorithms, data structures, and scientific programming for analysis of biological data.
- Experience in a Unix/Linux environment.
- Proficient in several of the following technologies: Go, R, Unix, Perl, Python, Java, Matlab, C/C++.
- Experience with common tools for
- NGS (BWA,GATK, STAR, Samtools, Picard, TopHat, Cufflinks, etc.)
- ChiP-seq (Bowtie, MACS, SICER, HOMER, etc.)
- Proteomics (mzR, mzLD, etc.)
- Metabolomics (metaboAnalyst, etc.)
- Genome annotation (e.g. Augustus)
- Experience in algorithm development for analysis of massively parallel sequencing data ().
- Experience with statistical analysis is strongly preferred.
- Strong scientific understanding of molecular and cellular biology, genetics and genomics.
- Candidates must demonstrate outstanding personal initiative.
- Excellent teamwork, time management and organizational skills.
- Ability to work independently in a multidisciplinary, fast-paced, dynamic and results-oriented environment.
- Ability to present data to a multidisciplinary audience in a clear and cohesive manner.
- Ability to meet deadlines and multitask efficiently is a must.