Anjani Kumari

ad3r01@r.postjobfree.com

Objective:

To work as a Bioinformatics and computational biologist in a research-oriented organization where I can utilize my education, skills and knowledge in computational biology to contribute to the organization's research goals and achievements.

Education:

Advanced Post Graduate Diploma in Bioinformatics and Computational Sciences, UCSD (2023)

Master’s in Biomedical Sciences, Rutgers University, New Jersey USA (2020)

Experiences and Knowledge:

More than 3+years in pharmaceutical industry cancer research field.

Have computational and programming skills, ideally with Python expertise, and experience in data mining of human whole genome and whole exome sequencing, large datasets in biotechnology field.

Knowledge of human genomic data and common open-source bioinformatics analysis tools, including UCSC genome browser

Experience in leveraging diverse public data repositories to extract valuable insights with statistical learning methods to make biological information understandable.

Experience with various toolkits used in bioinformatics for data processing, deep learning and machine learning of bio-molecular data along with experience with NGS or microarray genotype data.

Deep knowledge of cancer biology, cancer genomics related to its use in computational Biology.

Experience in computation methods and software tools employed for genome analysis and comparison, data visualization (ggplot2, plotly, etc.)

Knowledge of current genomics sequencing methods scrapping datasets from public repositories along with Github.

Handling of massive volumes of data through genomic sequencing along with abilities for troubleshooting.

Experience in statistical analysis skills using algorithm tools for data alignment eg. GATK, BWA, Bowtie, Sam tools, BCF tools used for aligning, read mapping, variant calling, annotation and pipeline construction along with sequence analysis and building tools for specified problems in bioinformatics.

Knowledge of cancer genomics somatic variant calling have experience working on 1000 Genomes project

Well acknowledged and have working experiences with various cloud platforms like GCP, Azure and AWS computing systems.

Proficient in programming languages as in R, SAS and Python, Perl relevant to bioinformatics/computational biology

Collaborated with wet lab scientists and molecular biologists, investigators in my previous job along with computational biologists, project managers, and external partners on experimental design, data analysis and interpretation and mechanistic understanding of target biology along with finding cancer biomarkers.

Use of resources like NCBI’s, Ensembl, BLAST web tools for sequence search, alignment, protein structure.

Experience conducting large-scale Genome-Wide Association Studies (GWAS) analyses, including local ancestry inference

Excellent oral and written communication skills to communicate to both scientific and broader audiences

Reviewing vast amount of literature related to the bioinformatics field for latest information in technologies and computing methods.

Ability to work on a cross-functional team in our highly collaborative environment, working with both computational and experimental scientist.

Have experience to work with DepMap and other open data sources to drive our target identification work streams

A deep passion for science and developing new methods in biomedical sciences and discoveries.

Previous work experience:

Research associate scientist: GSK 300 Technology Square, Cambridge, MA (Perkin Elmer-July2023)

Collaborating with computational biology, computational chemistry and molecular biology team for the target discovery and biomedical research resources targeting biomarkers in Oncology researches.

Strong understanding of single-cell RNAseq analysis workflow

Experience working with Proteomics team for data related to cancer studies.

Expertise in single cell genome-scale assays from both experimental and computational approaches

Developing immunoassays using flow cytometry including, UV- spectrometry and light scattering, with a focus on pharmacological profiling to support drug discovery.

Experience with Python, R statistical and computational analysis of genomic data.

Knowledge of human genomic data and common open source genomic analysis tools, chipseq, Bash, SQL language for various programming.

Used resources like NCBI Entrez for looking for protein structures and checking DepMap for selecting targeted cell lines for drug discovery research purposes.

Designing and conducting laboratory project and experiments including maintaining mammalian cell cultures.

Analyzed data using cloud computing systems, using various computational tools and doing data visualization using R software, plotting in ggplot and giving presentations in the team for the annotations and results.

Experience in Research analysis report results to researchers and scientists.

Participated in inter-team meetings to collaborate computational biologist team and Molecular biologist teams for analyzing data and discussing sources for data mining from repository.

Experience with conducting analysis in computing environments.

Currently support target validation, and handling programs for Research unit for new drug discovery Projects.

Previous Work Experiences:

Research Assistant Scientist – BMS (September 2022)

Responsible for the maintenance and expansion of several mammalian cell lines that includes cancer cell and tumor panel cell lines, using aseptic technique following BSL I and BSL II.

Performing several cell-based bioassays on mammalian cell and participate key activities associated with production cell line development including transfection, single cell cloning, high throughput screening of cells.

Seeding, harvesting, expansion and cryopreservation of cell lines including transfection single cell cloning and genetically modified cells.

Maintaining detailed and accurate documentation for all laboratory activities using custom organization owned software ad tools.

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