The Senior Scientist will be part of a team focused on bioinformatics and computational biology support of target selection, validation and mechanism of action investigations across multiple therapeutic areas such as gastrointestinal diseases and CNS. The Senior Scientist will apply expertise in bioinformatics and computational biology to analyze various types of molecular profiling and phenotype data for the identification and characterization of genes and pathways involved in normal and perturbed physiology. This information will be used to understand the molecular basis of disease pathology and the mechanism of action of drugs, and ultimately be used for selection and progression of drug targets.
- Performs advanced analysis of internal microarray, RNA-seq and other sequencing data in combination with publicly available genomics data by applying unsupervised and supervised machine learning algorithms to extract novel and biologically meaningful information.
- Applies statistical genetics analyses to internal and external genetics data to support or falsify target hypotheses.
- Integrates genomics, genetics, epigenetics and literature data to strengthen understanding of diseases and treatment perturbations.
- Utilizes multiple approaches for analyses of genes, pathways and networks.
- Provides relevant biological context to large lists of differentially expressed or regulated genes.
- Provides analysis and interpretation of data, specifically for the selection of new drug targets
- Writes study reports and presents data effectively in all settings and with participants of all levels of the organization.
EDUCATION, BEHAVIOURAL COMPETENCIES AND SKILLS:
- PhD or equivalent with Post Doc and at least 4 years of bioinformatics experience OR
- MS/MA with 14+ years of relevant experience OR
- BS/BA with 16+ years of relevant experience
- Has a solid background in basic cellular and molecular biology with an understanding of a range of disease areas including gastrointestinal diseases, immunology, inflammation and neurobiology. Exposure to a wide variety of therapeutic areas such as GI, CNS, or inflammation is a plus.
- Fluent in the use of R (Bioconductor), Python, and/or other languages commonly used for bioinformatics analysis. Must be expert in applying major bioinformatics tools.
- Must be expert in sequencing data analysis such as RNAseq, DNAseq, scRNA-seq, etc.
- Familiarity with microbiome data is a plus
- Understands the advantages and limitations of various types of human genetic datasets (e.g. GWAS, CNVs, Rare variants, etc.) and has hands on experience in using public human genetics and epigenetics databases.
- Is able to develop creative methods for integration of human genetic and epigenetic data with our proprietary mouse gene expression data to create a more robust drug target selection pipeline.
- Must be able to apply methods of unsupervised machine learning algorithms such as WGCNA, K-means, Hierarchical, DBSCAN, and/or Spectral clustering
- Must be able to apply methods of dimensionality reduction algorithms such as Non-negative Matrix Factorization (NMF), Principal Component Analysis (PCA), Independent Component Analysis (ICA), Manifold Learning and similar techniques.
- Must be familiar and able to apply advanced machine learning methods such as Hidden Markov Chain, Support Vector Machines, neural nets and deep learning algorithms.
- Strong communication and team working abilities to contribute in a team that operates as a unit on large projects.
- Must be able to apply network modeling methods
- Familiarity with text mining algorithms is a plus
- Carrying, handling and reaching for objects up to 25 lbs.
- Able to work in a lab environment
- Up to 20% travel, both domestic and internationally may be required.
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