Scientific Analyst
2 weeks ago
Excelra is looking for highly skilled and motivated computational biologist with expertise in automated Omics (NGS) pipeline engineering to join the Bioinformatics team involving projects related to raw sequence (scRNA-Seq/ATAC-Seq/WGS/Chip-Seq/RNA-Seq/Exome sequencing & genome assembly /annotations) analysis and downstream systematic interpretation. The successful candidate will be responsible for developing novel pipelines to optimize omics analysis implementation for the division’s core service areas including genomics data analysis, drug repurposing, biomarker identification, patient stratification, disease modelling and data integration.
Qualifications:
• Masters degree with 3-5 years of industrial experience in Bioinformatics, Computer Science, Computational Biology, or related field.
• Strong expertise in building end-to-end automated pipelines with workflow managers such as Nextflow.
• Strong track record of scRNA-Seq and other Omics (NGS) data analysis and downstream systemic interpretation are must.
• Good understanding of current best practices in computational biology data-management (NGS/Transcriptiomics/Microarray/Proteomics/Clinical-trials/Text-mining, etc.).
• Expertise in one or more programming/scripting languages such as R, Python, shell-script for complex data analysis.
• Strong background in population genomics, including GWAS, eQTL/pQTL analyses WES/WGS sequencing data analyses, and statistical analyses of rare and common variants.
• Familiarity with machine learning is an added advantage.
• Experience with Linux environment or cloud computing (AWS/GCP) is a plus.
• Experience with Relational database such as Postgres, MySQL, or Oracle
• Experience with version control systems such as GitHub.
• Ability to generate in-silico experimental workflows and in-depth knowledge in proprietary and public biological databases, methods, and tools.
• Ability to generate scientific hypothesis along with good scientific/technical communication skills would be preferred.
Roles & Responsibilities:
The selected candidate will be part of the Excelra’s Bioinformatics group. You will be responsible to work with a team in research data analysis in both prospective and retrospective manner to generate the novel hypothesis.
• Work with diverse customers/partners in drug discovery and development
• Work with multi-disciplinary team of PhD level scientists
• Responsible for day-to-day operational activities of Omics (NGS) related projects
• Keeping up to date with relevant scientific and technical developments
• Present the results and scientific hypotheses to internal and external stake holders
• Good communication and analytical skills combined with ability to recognize and implement project plans.
• Writing research papers, reports, reviews, and summaries
• Adjusts his/her behaviour in view of the situations and people, with an eye on the goal. Is open to other opinions, supports change, will step outside the comfort zone and try out new systems.
• Organises own work in function of the known priorities, procedures and situation, manages time, adheres to the deadlines and assesses external factors correctly in order to reach the goals within the set conditions.
• Values the goals and interests of the company within the area of expertise and organises work in such a way that the most effective contribution is achieved.
• Takes action before someone else asks this explicitly. Makes spontaneous suggestions for Improvement, assumes responsibility spontaneously.
• Develops his/her competencies and acquires new competencies and applies these. Keeps developing and broadening his/her horizon.
• Finds original out-of-the-box solutions for situations and proposes alternatives for existing solutions, without reinventing the wheel.
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India Excelra Full timeJob DescriptionExcelra is seeking a highly skilled computational biologist to join our Bioinformatics team. As a Scientific Data Analyst, you will be responsible for developing novel pipelines to optimize omics analysis implementation for our core service areas, including genomics data analysis, drug repurposing, biomarker identification, patient...
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