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Dry Lab related
• Design and conduct independent research under the direction of the Senior R&D Management
• 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 (MS) and epigenome towards differential cellular state analysis
• Derive pathway insights using both in-house generated and publicly available database that can be implemented in wet-lab to develop differentiated product
• 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
• Derive mechanistic insights and computational models using systems level simulations using pathway-based flux simulation, and (preferred) structural simulations including energy minimization and docking
• Actively contribute to development reports, scientific publications, patents, and regulatory documents and related submissions
Wet Lab related
• Perform various wet lab related work such as, cell culture, genomic analysis, RTPCR, ELISA. Cell-based assays, histology, flow cytometry, molecular biology experiments and various microscopic techniques including confocal studies
• Process human, rabbit and murine tissues, extract cells from primary origin and establish cultures to support various studies including multi-omics
Required Skills / Experience
• PhD in bioinformatics, structural biology, biostatistics, computer science, or related quantitative field (mandatory)
• 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
• Experience in RNASeq, Microarray, miRNA profiling and DGE analysis is required
• Pathway analysis experience using software like IPA will be highly regarded
• 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
• 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
