Modeling & Simulation expert
Career Path: AgileData
Type: Full Time preferred
Seniority: Mid senior level
Location: Cambridge or MetroWest, MA or New York, New Jersey
- Expertise in genetic, genomic and proteomics data analysis, including raw data processing and modeling of processed/normalized data, and familiarity with various technological platforms.
- Expertise in statistical methodologies such as predictive modeling and inference, machine learning methods, mixed effects models, multivariate analysis, etc.
- Relevant academic/industry experience on topics related to drug discovery, clinical genomics and other applications mentioned above.
- Strong programming and computing skills.
- Excellent communication, presentations and report writing skills, and the ability to explain complex technical details in simple language.
Ph.D. in biostatistics, with some coursework/experience in bioinformatics, biochemistry, molecular biology, genetics, and related subjects.Experience
5 years of related experience with demonstrated skills/accomplishments. Grade level and title will be commensurate with experience and expertise.Description
We provide statistical expertise for various groups in drug discovery, development sciences and for biomarker & genomics studies in early to late-stage clinical trials. Examples of applications/topics include in-vitro screening, in-vivo pharmacology, genomics (high-throughput mRNA expression arrays, CGH arrays, next generation sequencing, microRNA, genotype data, etc.), proteomics, imaging, and other biomarker data generated from pre-clinical and clinical studies, research and GLP assays used for measuring biomarkers, pharmacokinetics and immunogenicity response in preclinical and clinical studies and ADMET screening assays.Essential Duties & Responsibilities
Help build statistical capabilities in drug discovery & exploratory clinical/translational research by providing strategic input and leadership to analyze large and complex data sets derived from patient samples and pre-clinical models of disease. Objectives may be to support novel target identification, identifying markers of disease progression and treatment response and for patient selection or stratification in clinical trials. Sources of data will likely include Genomics (high throughput gene expression arrays, CGH arrays, next generation sequencing, microRNA, etc.), Proteomics, Imaging, and flow based cytometric assays, along with the clinical and pre-clinical pharmacology data.
Develop and maintain good working relationships with discovery and clinical scientists, statisticians, computational biologists, and external collaborators to drive program decisions as part of a multidisciplinary team.
Collaborate with external colleagues on consortia and other research projects relevant to biomarker discovery and evaluations.
Maintain and expand expertise in various computing tools to leverage internal and external data sets to drive decisions.
Proactively seek input and review from other experts within and outside the group on various projects and research activities, and share technical information when appropriate.
Mentor junior staff, proactively help with both their technical and career development, and seek general feedback and technical input from colleagues.
Modeling & Simulation expert
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