Postdoctoral Fellow, Computational & Tumor Cell Biology

Why Patients Need You

At Pfizer we deliver breakthroughs that change patients’ lives. Research and Development is at the heart of fulfilling Pfizer’s purpose as we work to translate advanced science and technologies into the therapies and vaccines that matter most. Whether you are in the discovery sciences, ensuring drug safety and efficacy or supporting clinical trials, you will apply cutting edge design and process development capabilities to accelerate and bring the best-in-class medicines to patients around the world.

What You Will Achieve

We are seeking a skilled and exceptionally driven computational biologist with hands-on wet bench expertise to join a team dedicated to uncovering and advancing novel therapies that target vulnerabilities in hormone-driven cancers. The postdoctoral fellow will work in an inter-disciplinary environment and will have the opportunity to advance cutting-edge cancer therapeutics through Pfizer’s robust oncology pipeline. The postdoctoral fellow will collaborate with renowned cancer centers and the African Caribbean Cancer Consortium to identify novel genetic determinants that impact the prognosis of hormone-driven cancers among those of African ancestry. The postdoctoral fellow will also collaborate with biologists, technologists, translational oncology leads, statisticians and computational biology colleagues on applying machine learning algorithms in drug discovery problems such as predicting drug response and translating findings from in vitro, to in vivo and patient data. The postdoctoral fellow is expected to utilize cutting-edge computational methods for integrative analysis and biological interpretation of high-dimensional molecular data. The successful candidate should have strong biological and computational background, with proven capability of solving complex problems by creating innovative analytical solutions.    

How You will Achieve It

Successful Candidates will be expected to:

• Lead and contribute to publication on hormone-driven cancers
• Drive computational analysis of large-scale molecular data from patient dataset in collaboration with teams
• Conduct in silico analysis to address questions such as identifying somatic drivers of cancer using tumor-derived molecular OMICs data.
• Spear-head collaborations with external colleagues to analyze molecular data.  
• Actively participate in multidisciplinary project teams to formulate data-driven, actionable hypotheses.
• Apply machine learning algorithms for drug discovery.
• Contribute effectively to a shared codebase that can be leveraged broadly for multiple applications.

Qualifications:

Must-Have

• Ph.D. or equivalent in computational biology, genetics/genomics, biostatistics or a related field.
• Successful record of scientific accomplishments as indicated by scientific publications and/or presentations. At least one first-author publication in peer-reviewed scientific journals.
• Willingness to make a minimum 2-year commitment.
• No more than 2 years of post-degree experience.

• Proficiency in statistical analysis using R, a scripting language (Perl or Python) and working with the UNIX/LINUX environment. 
• Deep knowledge of high throughput molecular profiling and experience in mining “big OMICS data”, e.g. RNA-Seq, WES, CRISPR etc. 
• Strong background in cancer genomics is highly desired.
• Proficiency with foundational cell and molecular biology techniques; for example: vector design & cloning, CRISPR-mediated gene editing, stable cell line generation, qRT-PCR, Western blotting, ELISA, IP/ChIP, NGS sample preparation, 2D/3D proliferation assays. 
• Expertise applying machine learning methods to multi-omics/high-dimensional data analysis is a plus.

• Track record of innovative and proactive problem solving, preferably in cancer biology and medicine. 
• Experience in productive collaboration with bench scientists is highly desirable.
• Ability to multi-task, effectively communicate (oral and written) and work with diverse expertise teams.

PHYSICAL/MENTAL REQUIREMENTS

Ability to perform mathematical calculation and ability to perform complex data analysis. Ability to work in the laboratory.

OTHER JOB DETAILS

• Must have work authorization in the US.
• Work Location Assignment: On Premise. On Premise colleagues work in a Pfizer site because it’s needed to get their job done. They may have flexibility to work remotely from time to time, but they are primarily on-site.