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Paid Internship
Work Mode
Time Spent
Required Degree
Duration

12Open Positions

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Internship in Innovation & Sustainability

Roche
Found 1 week ago
Location
Basel, Switzerland
Time
Full-time
Work Mode
On-site
Salary
Not disclosed
Visa Help
Not disclosed
Last Verified
1 week ago

Education

  • Master
  • PhD

Skills & Qualifications

Technical Skills

  • Pharmacoepidemiology
  • Epidemiology
  • Biostatistics
  • Data Science
  • Health Informatics
  • Public Health
  • SQL
  • R programming
  • Python
  • Git
  • ICD-10
  • observational study designs
  • causal inference frameworks

Soft Skills

  • Detail-oriented
  • analytical
  • independent
  • collaborative
  • communicate technical findings clearly

Job Description

Our Global Internship Programme in Innovation & Sustainability (#IP2TIS) offers a unique opportunity for passionate individuals to gain hands-on experience in the pharmaceutical industry while making a positive impact on the world. Are you ready to join a global network spanning 20+ countries, where bright minds collaborate to tackle real-world challenges in Innovation & Sustainability? Do you want to work on impactful projects, shape the future, and drive change from within? As an intern, you will contribute to closing the evidence gap for a vulnerable patient population by evaluating mother-child linkages within a novel real-world data source. The project aims to establish a readiness framework for drug safety research. During the three-month internship, you will deliver a technical assessment of the cohort and develop clinical phenotyping algorithms and pilot causal inference methodologies for pregnancy-related analyses. Your work will establish scalable pipelines for generating clinically relevant evidence leveraging target trial emulation, ultimately supporting more equitable maternal and pediatric health outcomes. This role offers the opportunity to lead a high-impact project at the intersection of real-world data and patient-centered evidence generation for drug safety.

Requirements

  • You are enrolled or have completed your Master’s or PhD studies at a university, preferably in the field of Pharmacoepidemiology, Epidemiology, Biostatistics, Data Science, Health Informatics, or Public Health within the last 12 months and are interested in applying your knowledge in a modern working environment as part of an internship of at least 3 months.
  • Proficient in SQL and experienced in querying large-scale databases and handling complex data extractions
  • Strong in R programming; experience with Python and Git for version control is an advantage
  • Familiar with medical vocabularies such as ICD-10 and with observational study designs, including common sources of bias
  • Knowledgeable in causal inference frameworks, including the management of time-varying exposures and outcomes
  • Detail-oriented, analytical, independent, collaborative, and able to communicate technical findings clearly in English

Related Field

  • AI & Machine Learning

Related Subfield

  • Applied Machine Learning

Languages

  • English

Nice to Haves

  • experience with Python and Git for version control
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