-
well as the Portfolio Operations and Program Management organizations. The position will report to the Chief Development Officer. JOB RESPONSIBILITIES : Responsible for leading and managing the PTL team as
-
therefore expected that the candidate will have deep expertise in computational and data science methods, but also be able to bridge that knowledge to fundamental questions of biology and clinical impact
-
and scalable Active Pharmaceutical Ingredient (API) crystallization processes for use at manufacturing plants across Pfizer's network. You will apply chemical engineering principles, computational
-
Engineering or related Mechatronics discipline (or within 6 months of completing a program) or an B.S. with 3+ years' experience in a related field. No industrial experience necessary. Experience with robotic
-
. MINIMUM QUALIFICATIONS • Bachelor's degree or above or equivalent experience in a scientific or business related discipline required; Degree in Informatics, or Computer science, or Statistics, or related
-
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
-
impact of the group. Qualifications Ph.D. in Chemical Engineering, Organic Chemistry or Mechatronic Engineering related discipline (or within 6 months of completing a program) or an Msc with 3+ years
-
+ years of experience • Degree preferably in engineering, economics, statistics, computer science, or related quantitative field. • Preferred experience in Applied Econometrics, Statistics, Data Mining
-
• Develop effective relationships with external thought leaders in RWD/RWE, comparative effectiveness research, health informatics, and data sciences so as to maintain an extensive understanding of external
-
of other colleagues to achieve meaningful outcomes and create business impact. Degree in Computer Sciences, Statistics, Clinical Informatics or similar Relevant certification &/or work experience in data