Disease Modeling Scientist I2O

Job description

·  Job facts

The role of the I2O Disease Modeling Scientist is to provide state of the art disease modeling and simulation (M&S) support to the Inflammatory, Infectious and Ophthalmology(I2O) Disease Translational Area (DTA) disease modeling strategies. This is accomplished by the development of empirical and/or mechanistically-based drug disease models with formal integration of the (patho)physiology of disease,clinical data and drug targets. He/she will contribute to supportthe DTA Modeling Leader(s) through disease modeling initiatives that are alignedwith the DTA key priorities.

Major Responsibilities and Accountabilities:

•Accountable for the development of Disease Modelsrelevant to the DTA Disease Modeling strategy
•Provide support toPharmacometrician(PHME) for the implementation of drug disease models (that he/she developed) across the projects within the DTA

• Collaborate effectively with internal modeling groups (e.g. DTA,PharmaScience)

•Accountable to identify suitable external collaborators and opportunities to adapt existing disease modeling work in order to support & impact drug development decision making and DTA projects
•Responsible for presenting and defending the disease modeling aspects to theClinPharm sub-team and DTA stakeholders.

•Identifies opportunities for utilizing the Roche Postdoctoral Fellowship program to accomplish diseasemodelingobjectives

Qualifications:

You hold a PhD in the fields of statistics, computational biology, applied mathematics or physics applied to life sciences (obtained within the last 4 years) with at least 2 years of experience in the planning and conduct of Disease Modeling and Simulation projects (preferably in a pharmaceutical industry setting).

Competencies Required:

•Broad analytic skills (e.g. statistical and machine learning methods, dynamical models), with ability to understand and develop mathematical models and to implement them in the R statistical programming language

• Experience in building and analyzing longitudinal clinical predictive model applied to health care data and drug development

•Strong knowledge of Bayesian and Non-Linear Mixed Effects (NLMEs) methods is required and proficiency in Bayesian and NLME software languages (e.g. Stan,Monolix,) is highly desired.
•Solid expertise in model qualification and validation (e.g. sensitivity analysis, quantification of prediction uncertainty, diagnostic plots, cross-validation,etc)
•Expertise in exploratory data analysis (including building/evaluating statistical models from data)
•Good knowledge of the Drug Discovery and Development process including Pharmacokinetics/Pharmacodynamics (PK/PD).
•Highly effective team work and interpersonal skills (globally, internal and externally)
•Ability to explain complex M&S concepts and their impact on drug development program to non-modeler colleagues
•Ability to establish and maintain effective working relationships with a broad range of other professionals, including key opinion leaders from academia,from different cultural backgrounds
•Flexibility and confidence to handle ambiguities, changing demands and changing priorities
•Ability to learn from experience – seeking feedback and modifying behaviour in light of the feedback received
•Highly effective verbal and written communication/ presentation skills with proven track record of publishing in peer reviewed journals
•Can design apresentation/discussion to educate, convince and influence the target population, regardless of impact of conclusions.

·  Who we are

At Roche, 94,000 people across 100 countries are pushing back the frontiers of healthcare. Working together, we've become one of the world's leading research-focused healthcare groups. Our success is built on innovation, curiosity and diversity.

Roche is an equal opportunity employer.