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Paid Internship
Work Mode
Time Spent
Required Degree
Duration

24Open Positions

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Software Engineering Intern - Data Architecture (Bioanalytics)

Roche
Found 4 days ago
Location
Basel, Switzerland
Time
Full-time
Work Mode
On-site
Salary
Not disclosed
Visa Help
Only EU/EEA
Last Verified
4 days ago

Education

  • Bachelor
  • Master
  • PhD

Skills & Qualifications

Technical Skills

  • Python
  • R
  • data science
  • R-Shiny
  • SQL
  • backend solutions
  • API development
  • Git
  • lab automation
  • robotics

Soft Skills

  • analytical skills
  • problem-solving skills

Job Description

Within Roche Pharma Research & Early Development (pRED), the ADME (Absorption, Distribution, Metabolism, and Excretion) Chapter plays a crucial role in understanding and predicting the effects of new medicines on the human body. We focus on key mechanisms of drug behavior, leveraging cutting-edge techniques such as 3D cell culture, in silico modeling, and lab automation to accelerate research and development. We are expanding our capabilities in lab automation and digitalization to enhance our processes and outcomes. You'll contribute to impactful projects focused on lab automation and digitalization, with exciting opportunities to dive into data science applications. For this internship, your work will be two-fold: developing a digitalization platform for bioanalytics data, and developing a specific Data Analysis (DA) pipeline project in Genedata Screener. Specifically, you will: * Work with interdisciplinary teams to automate and digitalize workflows, analyze data, and support ongoing research initiatives. * Build a front-end & API integration for a new database storing bioanalytics data. * Build a data analysis pipeline by translating an existing R-Shiny application into a Genedata Screener workflow. * Gain hands-on experience in developing and implementing automated assays and workflows. * Contribute to projects focused on digitalization and data management. * Learn about cutting-edge technologies and methodologies used in pharmaceutical research and development.

Requirements

  • You hold a bachelor's or master's degree in Biology, Chemistry, Computer Science, Data Science, or a related field, or are currently enrolled in a relevant Master's or PhD program.
  • You have strong experience in programming languages such as Python or R, and ideally a basic understanding or interest in data science.
  • You have practical experience with R-Shiny and a strong interest in platform integrations (experience with Genedata Screener is highly preferred).
  • You have experience with SQL, backend solutions, and API development.
  • You have experience working with version control systems (Git).
  • You have experience or interest in lab automation and robotics.
  • You possess strong analytical and problem-solving skills.
  • You have a good command of spoken and written English.

Related Field

  • Software Engineering

Related Subfield

  • Backend Engineering

Languages

  • English

Nice to Haves

  • Genedata Screener
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