Scientist, Bioinformatics
InVitro Cell Research, LLC
Summary
We're hiring Bioinformatics Scientists with strong backgrounds in computational biology and data science. A deep understanding of both biology and machine learning is required. The position's goals are varied, but include using personalized biomarker discovery and integrative-omics to diagnose "hard-to-diagnose" diseases.
Job description
In this position at ICR, you'll get to:
- Conduct complex bioinformatics analyses on large genomics, transcriptomic, proteomic, metabolomic, and lipidomic datasets from biofluids and cell lines
- Engage in multi-omic integration under a personalized medicine paradigm
- Discover personalized biomarkers to aid in unraveling complex and obscure phenotypes
Please apply if you have:
- An MS or PhD in a Biomedical Science and extensive experience with computational biology, bioinformatics and data science
- Experience incorporating AI tools into bioinformatics workflows
- Expertise in multi-omics integration, systems biology, network medicine, precision and personalized medicine
- Expertise in perturbation analysis and pathway enrichment analysis (eg. KEGG, Reactome, MSigDB)
- Machine learning skills (eg. LR, SVM, RF, XGBoost) and extensive experience with: Bayesian/probabilistic modeling, network-based sample similarity algorithms and factorization methods, data cleaning, such as batch effect removal and imputation, and data transformation and visualization
- A solid statistical foundation
- Expertise programming machine learning and statistical pipelines, preferably in Python
- GitHub repository showing your work, preferably linked to publications
Ideally, you'll also have experience with:
- iOS app development
- R programming
- Linux environments
- Outlier detection
And you'll need:
- Ability to work in the United States without sponsorship
- A can-do attitude and a friendly, easygoing personality
Requirements
- MS or PhD in a Biomedical Science
- Extensive experience with computational biology, bioinformatics and data science
- Experience incorporating AI tools into bioinformatics workflows
- Expertise in multi-omics integration, systems biology, network medicine, precision and personalized medicine
- Expertise in perturbation analysis and pathway enrichment analysis (eg. KEGG, Reactome, MSigDB)
- Machine learning skills (eg. LR, SVM, RF, XGBoost)
- Experience with Bayesian/probabilistic modeling
- Experience with network-based sample similarity algorithms and factorization methods
- Data cleaning such as batch effect removal and imputation
- Data transformation and visualization
- Solid statistical foundation
- Expertise programming machine learning and statistical pipelines, preferably in Python
- GitHub repository showing your work, preferably linked to publications
- Ability to work in the United States without sponsorship
- A can-do attitude and a friendly, easygoing personality
Benefits
- Relocation Expenses
- Competitive Salaries
- Cutting-edge Research Environment
Company overview
InVitro Cell Research, LLC is a biotechnology company specializing in advanced cell biology research and development. The company focuses on in vitro cell culture technologies, cellular models, and innovative research methodologies for biomedical applications. As a research-focused organization, InVitro Cell Research likely engages in developing novel cell-based assays, tissue engineering approaches, and cellular systems for drug discovery and basic research. The company's work encompasses various aspects of cell biology including stem cell research, primary cell culture, 3D cell culture systems, and specialized cellular models for disease research. Their expertise in in vitro methodologies positions them as a valuable partner for pharmaceutical companies, academic institutions, and research organizations seeking advanced cellular research capabilities. The company contributes to the broader biotechnology ecosystem by providing specialized research services, developing proprietary cell-based technologies, and advancing scientific understanding of cellular processes relevant to human health and disease.