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Internship in Innovation & Sustainability - For students in the field of Computational Chemistry, Data Science, Computer Science or a related quantitative discipline

Internship in Innovation & Sustainability - For students in the field of Computational Chemistry, Data Science, Computer Science or a related quantitative discipline

Internship in Innovation & Sustainability - For students in the field of Computational Chemistry, Data Science, Computer Science or a related quantitative discipline

Internship in Innovation & Sustainability - For students in the field of Computational Chemistry, Data Science, Computer Science or a related quantitative discipline

Roche

Pharmazeutische Produkte, Arzneimittel

Basel

  • Art der Beschäftigung: Studierende
  • Vor Ort
  • Zu den Ersten gehören

Internship in Innovation & Sustainability - For students in the field of Computational Chemistry, Data Science, Computer Science or a related quantitative discipline

Über diesen Job

JOB DESCRIPTION

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.

The Position

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.

The Opportunity

  • Collect, organize, and prepare data for benchmarking machine learning models on relevant oligonucleotide molecular properties

  • Explore and compare different featurization techniques and algorithm types for key optimization endpoints

  • Adapt and test uncertainty quantification methods on existing and newly developed models

  • Integrate the best-performing models into existing machine learning operationalization systems and extend them to include uncertainty quantification metrics

  • Collaborate with stakeholders and communicate progress and findings to the wider scientific community

Who You Are

You are enrolled or have completed your Master’s or PhD studies at a university, preferably in the field of Computational Chemistry, Data Science, Computer Science or a related quantitative discipline 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.

Furthermore you are

  • Proficient in Python and experienced with statistical, machine learning, and deep learning frameworks such as Scikit-learn and PyTorch

  • Knowledgeable in featurization methods, model architectures, and uncertainty quantification approaches

  • Experienced in building, evaluating, and operationalizing machine learning models, ideally for chemistry or biology applications

  • Familiar with software development concepts such as backend, frontend, deployment and system integration

  • Able to critically use AI agents for coding and scientific research

  • An independent, curious, and collaborative communicator with excellent spoken and written English

If you meet most but not all qualifications, we still encourage you to apply.

Additional information

The internship is expected to start between 1 and 16 July 2026 and will last at least 3 months.

For more information about IP2TIS and to explore other opportunities within the programme, please visit go.roche.com/ip2tis_26._

Who we are

A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact.

Let’s build a healthier future, together.

Roche is an Equal Opportunity Employer.

Unternehmens-Details

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Roche

Pharmazeutische Produkte, Arzneimittel

10.001 oder mehr Mitarbeitende

Basel, Schweiz

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