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Paid Internship
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Time Spent
Required Degree
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24Open 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

  • Python
  • Scikit-learn
  • PyTorch
  • featurization methods
  • model architectures
  • uncertainty quantification approaches
  • building
  • evaluating
  • operationalizing machine learning models
  • software development concepts
  • backend
  • frontend
  • deployment
  • system integration
  • AI agents for coding
  • scientific research

Soft Skills

  • independent
  • curious
  • collaborative communicator
  • excellent spoken and written English

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 a project focused on building a reliable AI-driven design framework for oligonucleotide research. The project aims to establish a scientifically grounded approach for benchmarking oligonucleotide featurization methods for machine learning models and integrating uncertainty quantification into the AI-guided design process, helping researchers make higher-confidence decisions in silico. Within your first 3 months, you are expected to help create a benchmarking leaderboard and a Python-based framework for uncertainty quantification. Your work will help reduce trial-and-error laboratory cycles, lower the need for physical synthesis and screening, and support more sustainable and efficient RNA drug discovery. This internship offers the opportunity to work at the forefront of applied AI in oligonucleotide research with direct impact on both scientific innovation and sustainability.

Requirements

  • Python
  • Scikit-learn
  • PyTorch
  • featurization methods
  • model architectures
  • uncertainty quantification approaches
  • building
  • evaluating
  • operationalizing machine learning models
  • software development concepts
  • backend
  • frontend
  • deployment
  • system integration
  • AI agents for coding
  • scientific research
  • independent
  • curious
  • collaborative communicator
  • excellent spoken and written English

Related Field

  • AI & Machine Learning

Related Subfield

  • Applied Machine Learning

Languages

  • English
▶Apply Now

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