Research Engineer - Computational Biology

Job Profile:

• Develop detailed study plans, perform required studies, analyse data, and interpret results. Summarize experimental data timely and assist in drafting reports, figures, results, etc., for scientific and business presentations
• Process and analyse multi-omics biological data for various projects, including transcriptome, proteome and epigenome towards differential cellular state analysis
• Perform mapping and building gene regulatory network (GRN) from biological data analysis using GO and other databases/ knowledge repertoires
• Correlation of sequence and structure to function
• Map cellular circuitry, using correlation and causality network and identify key cell signalling pathways
• Mechanistic insights and computational models using systems level simulations using pathway-based flux simulation, and (preferred) structural simulations including energy minimization and docking
• Develop analytical tools/codes to streamline data acquisition and analysis and interpretation.
• Perform various cell culture, biochemical characterization-related studies, genomic analysis, RTPCR, assays, histology, flow cytometry, advanced imaging and various microscopic techniques including confocal studies
• Actively contribute to development of reports, scientific publications, patents, regulatory documents and other related submissions
• Additional research studies in the lab, as required

Required Skills / Experience:

• PhD in bioinformatics, computational biology, structural biology, biostatistics, computer science, or related quantitative field
• Experience working with single-cell data and/or good understanding of the signal and noise in single-cell data. Experience with multi-omics data is a plus
• Demonstrated ability to assess assay performance and derive biological insights by evaluating single-cell sequencing results using data visualizations and statistical tests
• Functional experience coding in at least one programming language (Python, Perl, C++/C) and a statistical computing language (R, S, etc.)
• Strong experience in statistics, data analysis and pipeline development
• Demonstrated ability to troubleshoot complex problems
• Ability to contribute independently and collaboratively, and to excel in a fast-paced environment
• Excellent communication and teamwork skills to work with both experimental and computational scientists in a collaborative environment

Desirable qualifications considered as plus:

• Machine Learning, statistical analysis data science methods development for single cell multi-omics
• Experience with NGS-based assay development and optimization
• Solid understanding of molecular and cell biology with prior experience in stem cell biology, stem cell based secreted cell modulators including exosomes and bioprocessing will be preferred