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GlaxoSmithKline (GSK) has a two-year position for a highly motivated pharmacometrician to join our global department of Clinical Pharmacology Modelling & Simulation. This is an excellent opportunity to apply pharmacometrics to accelerating the delivery of new medicines to patients by enhancing drug program efficiency and business decision quality.

The main project will be applying Item Response Theory to rating scales associated with neurodegenerative diseases. Embedded in an organization where we develop therapies of various modalities for a broad range of indications at stages from pre-clinical to post-approval development, you will also have tremendous opportunities for broad exposure to drug discovery and development.

• Plan, conduct and report item response modelling, disease progression modelling, simulation-based trial design and dose-exposure-response analysis to maximise data use, trial efficiency and analytical power
• Contribute to clinical trial design, and discuss modelling strategy and outcome to project teams and governance boards
• Promote model-informed drug discovery and development through internal/external collaboration, journal publication and conference presentation

Working in a department with diverse expertise and with multi-discipline teams, you will enjoy a highly supportive environment for innovation, influence and growth. The ideal primary work location will be in London (UK) or Philadelphia (USA) area, though there is flexibility for the right candidate. Interested persons are encouraged to apply online or contact Chao Chen for more information.

Chao Chen
Clinical Pharmacology Modelling & Simulation, GlaxoSmithKline

Closing date for applications:25th March 2019

During the course of your application you will be requested to complete voluntary information which will be used in monitoring the effectiveness of our equality and diversity policies. Your information will be treated as confidential and will not be used in any part of the selection process.

If you require a reasonable adjustment to the application / selection process to enable you to demonstrate your ability to perform the job requirements please contact 0808 234 4391. This will help us to understand any modifications we may need to make to support you throughout our selection process.

When applying for this role, please use the 'cover letter' of the on-line application to describe how you meet the competencies for this role, as outlined in the job requirements above. The information that you have provided in your cover letter and CV will be used to assess your application.

Thank you for your interest in this opportunity.


Why You?Basic qualifications:
• Advanced training in pharmacometrics or statistics, and experience in using modelling/simulation to solve practical problems in industry or academia
• Familiarity with item response theory, longitudinal disease modelling and model-based meta-analysis; proficiency with software tools NONMEM, Monolix, R and SAS
• Aptitude for productive collaboration in a multi-discipline team, effective communication and taking personal accountability for timely delivery of results

Preferred qualifications:
See above.

Why GSK?:
At GSK, our mission is to improve the quality of human life by enabling people to do more, feel better and live longer. Our three world-leading businesses research and deliver innovative medicines, vaccines and consumer healthcare products. We need a talented and motivated workforce to deliver against our strategy. To achieve this, we strive to attract the best people and to create an environment that empowers and inspires.

Contact information:
You may apply for this position online by selecting the Apply now button.

If you require an accommodation or other assistance to apply for a job at GSK, please contact the GSK HR Service Centre at 1-877-694-7547 (US Toll Free) or +1 801 567 5155 (outside US).GSK is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive equal consideration for employment without regard to race, color, national origin, religion, sex, pregnancy, marital status, sexual orientation, gender identity/expression, age, disability, genetic information, military service, covered/protected veteran status or any other federal, state or local protected class.

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