Job Details
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The Opportunity
Description
We're looking for a Postdoctoral Computational Biology Scientist, working in Pharmaceuticals and Medical Products industry in Cambridge, Massachusetts, United States.
- Performs advanced analysis of DNA-seq, RNA-seq, ChIP-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.
- Integrates genomics, genetics, epigenetics and literature data to strengthen understanding of diseases and treatment perturbations.
Our ClientOur client is an award-winning clinical development company. Improving lives globally with 20+ years experience in clinical research and strategic resourcing. Elevating results with proven strategies, comprehensive solutions, and customized delivery models.
Serving pharmaceutical, biopharmaceutical, biotechnology, and medical device organizations.
Strong relationships provide you connections and access to great opportunities. Industry expertise sets you up for success with helpful insights, career coaching, and professional training. Grow and learn while you put your skills to work.
Experience Required for Your Success- PhD or equivalent in bioinformatics, computational biology, or a related field
- Strong programming skills in R, Python, and/or other languages commonly used for bioinformatics analysis
- Expert in applying major bioinformatics tools
- Understanding of the advantages and limitations of various types of human genetic datasets (e.g. GWAS, CNVs, Rare variants, etc.)
- Hands-on experience in using public human genetics and epigenetics databases
- Solid background in basic cellular and molecular biology with an understanding of neurological disorders
- Strong communication and team working abilities to contribute in a team that operates as a unit on large projects
- Expert in sequencing data analysis such as RNAseq, DNAseq, scRNA-seq, etc.
- Deep knowledge and working experience to apply advanced machine learning methods such as Hidden Markov Chain, Support Vector Machines, neural nets and deep learning algorithms
- Familiarity with databases such as UK Biobank, AMP-AD, PPMI preferred
- Background in Neuroscience preferred
What Do You Think?Does your experience reflect what it takes to be successful in this role? Do the work and challenges get you excited about what's possible?