F. Hoffmann-La Roche AG
Internship in Innovation & Sustainability(m/w/x)
Full-timeInternshipOn-site
Kaiseraugst
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RORoche
Internship in Innovation & Sustainability - For students in the field of Data Science, Computer Science / Software Engineering, Bioinformatics / Computational Biology, or Artificial Intelligence / Machine Learning(m/w/x)
Kaiseraugst
Full-timeInternshipOn-site
AI/ML
Data Science
Nejo AI Summary
Building large-scale biomedical knowledge graphs from disease abstracts. Python proficiency for data manipulation required. Internship of at least 3 months.
Requirements
- Student in Data Science, Computer Science/Software Engineering, Bioinformatics/Computational Biology, or AI/Machine Learning
- Enrolled or completed Master's/PhD in Data Science, Computer Science, Bioinformatics/Computational Biology, or AI/Machine Learning within last 12 months
- Interest in applying knowledge in modern working environment
- Internship of at least 3 months
- Proficiency in Python for data manipulation
- Experience with Pandas and NumPy
- Experience with Hugging Face Transformers
- Experience fine-tuning language models
- Experience with PyTorch or TensorFlow
- Familiarity with knowledge graphs
- Experience with biomedical datasets (advantageous)
- Experience with medical ontologies (advantageous)
- Comfortable using Git
- Writing clean, documented, reusable code
- Analytical communication skills
- Proactive attitude
- Detail-oriented communication skills
- Strong English skills
- Encouraged to apply even if not meeting all qualifications
Tasks
- Contribute to an automated biomedical knowledge graph project
- Implement a fine-tuning pipeline for small language models
- Develop an entity resolution workflow
- Build a large-scale knowledge graph from disease-relevant abstracts
- Create a performance report and integration demo
- Support faster evidence synthesis and research insights
- Develop NLP pipelines using efficient small language models
- Curate and process biomedical data for model training
- Design and construct large-scale knowledge graphs
- Validate complex scientific information organization
- Build workflows for biomedical concept mapping
- Standardize biomedical terminology
- Evaluate AI model performance
- Document technical findings and insights
- Collaborate with an interdisciplinary team
- Translate methods and datasets into proof-of-concept tools
Education
- Currently in higher education
Languages
- English – Business Fluent
Tools & Technologies
- Python
- Pandas
- NumPy
- Hugging Face Transformers
- PyTorch
- TensorFlow
- Git
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Roche and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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RORoche
Internship in Innovation & Sustainability - For students in the field of Data Science, Computer Science / Software Engineering, Bioinformatics / Computational Biology, or Artificial Intelligence / Machine Learning(m/w/x)
Kaiseraugst
Full-timeInternshipOn-site
AI/ML
Data Science
Nejo AI Summary
Building large-scale biomedical knowledge graphs from disease abstracts. Python proficiency for data manipulation required. Internship of at least 3 months.
Requirements
- Student in Data Science, Computer Science/Software Engineering, Bioinformatics/Computational Biology, or AI/Machine Learning
- Enrolled or completed Master's/PhD in Data Science, Computer Science, Bioinformatics/Computational Biology, or AI/Machine Learning within last 12 months
- Interest in applying knowledge in modern working environment
- Internship of at least 3 months
- Proficiency in Python for data manipulation
- Experience with Pandas and NumPy
- Experience with Hugging Face Transformers
- Experience fine-tuning language models
- Experience with PyTorch or TensorFlow
- Familiarity with knowledge graphs
- Experience with biomedical datasets (advantageous)
- Experience with medical ontologies (advantageous)
- Comfortable using Git
- Writing clean, documented, reusable code
- Analytical communication skills
- Proactive attitude
- Detail-oriented communication skills
- Strong English skills
- Encouraged to apply even if not meeting all qualifications
Tasks
- Contribute to an automated biomedical knowledge graph project
- Implement a fine-tuning pipeline for small language models
- Develop an entity resolution workflow
- Build a large-scale knowledge graph from disease-relevant abstracts
- Create a performance report and integration demo
- Support faster evidence synthesis and research insights
- Develop NLP pipelines using efficient small language models
- Curate and process biomedical data for model training
- Design and construct large-scale knowledge graphs
- Validate complex scientific information organization
- Build workflows for biomedical concept mapping
- Standardize biomedical terminology
- Evaluate AI model performance
- Document technical findings and insights
- Collaborate with an interdisciplinary team
- Translate methods and datasets into proof-of-concept tools
Education
- Currently in higher education
Languages
- English – Business Fluent
Tools & Technologies
- Python
- Pandas
- NumPy
- Hugging Face Transformers
- PyTorch
- TensorFlow
- Git
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Roche and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
About the Company
Roche
Industry
Pharmaceuticals
Description
The company is dedicated to advancing science and ensuring access to healthcare for everyone.
Not a perfect match?
- F. Hoffmann-La Roche AG
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