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2014 Boehringer Ingelheim BDM Summer Boot Camp

The pharmaceutical company Boehringer Ingelheim was founded in 1885 by Albert Boehringer (1861-1939) in Ingelheim am Rhein. From its beginnings in 1885 when it employed just 28 people in Nieder-Ingelheim, the company has since become a global enterprise.

As part of research and development activities for innovative drugs, the company focuses primarily on the therapeutic areas of cardiovascular disease, respiratory diseases, diseases of the central nervous system, metabolic diseases, virological diseases and oncology.

The Boehringer Ingelheim group is one of the world′s 20 leading pharmaceutical companies. Headquartered in Ingelheim, Germany, it operates globally with 140 affiliates and more than 46,000 employees. Since it was founded in 1885, the family-owned company has been committed to researching, developing, manufacturing and marketing novel medications of high therapeutic value for human and veterinary medicine.

Degree / Education：Graduate students

Tasks and outcome of the BI BDM Summer Boot Camp:

With provided information related to preliminary Biometrics and Data Management production tasks, candidates will work as groups to fulfill Clinical Data Management, statistics and statistical programming activities which will include definition and implementation of plausibility checks, data review and issuing of data queries as part of the data cleaning process, design of a statistical analysis plan / table shells, analysis data build, reporting and trial review and analyses. By doing so, candidates will get a basic picture of how Biometrics and Data Management runs.

Required Capabilities:

Good organizational skills, problem-solving abilities, time management skills, initiative, detail oriented, precise, analytical and be able to work with and understand data. Good reading, written and oral communication skills in English. Flexibility and ability to work on several assignments simultaneously. Must be able to work independently as well as part of a team. Must have some basic SAS knowledge. Scientific and data processing experiences are pluses.

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