Statistics & Decision Sciences and Manufacturing and Applied Statistics Intern

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow and profoundly impact health for humanity.

Caring for the world, one person at a time has inspired and united the people of Johnson & Johnson for over 130 years. We embrace research and science -- bringing innovative ideas, products and services to advance the health and well-being of people.

Johnson & Johnson is the world's most comprehensive and broadly-based manufacturer of health care products, as well as a provider of related services, for the consumer, pharmaceutical, and medical devices markets. There are more than 250 Johnson & Johnson operating companies employing over 125,000 people and with products touching the lives of over a billion people every day, throughout the world. If you have the talent and desire to touch the world, Johnson & Johnson has the career opportunities to help make it happen.

J&J Innovative Medicine Research & Development, L.L.C, a member of Johnson & Johnson's Family of Companies, is recruiting for Manufacturing and Applied Statistics (MAS) and Statistics & Decision Sciences (SDS) Summer across multiple European locations. Virtual internships are potentially available. For MAS and SDS, summer internships are available for graduate students working towards a degree in Computer Science, Data Science, Statistics, or a related field. There are up to 2 positions available.

Students will have the opportunity to work with practicing statisticians and computing science specialists and to learn about practical, applied AI and statistical needs and solutions specific to clinical or nonclinical pharmaceutical industry settings. Our teams benefit from the student's academic training and in turn contribute to the further professional development of the student as well as have a first-hand opportunity to evaluate the student's potential for future employment.

Role Overview:

In this role, students will be involved in activities such as:

LLM Fine-Tuning:

• Fine-tune a pre-trained LLM on historical pre-PPQ and PPQ data using supervised learning.
• Explore the use of embedding-based vector search to enable accurate document retrieval.

Microservices Development:

• Implement the advisor functionality as RESTful APIs/microservices.
• Ensure seamless integration with the MaSta UI and other JnJ applications/platforms.

Database Integration:

• Convert Truvault documents (stability analysis, pre-PPQ, and PPQ reports) from PDF/DOCX into text, generate word embeddings, and store them in a vector database for efficient semantic search.
• Enable the AI advisor to process user prompts, query the vector database, and retrieve relevant results while ensuring data security and confidentiality.

Testing & Deployment:

• Perform rigorous testing to validate the system's performance.
• Deploy the advisor feature within the MaSta UI, ensuring user-friendly access.

Qualifications

• Be enrolled in an accredited European college/university pursuing the following degrees: Bachelor’s, master’s or PhD Computer Engineering, Data Science, Computer Science, Mathematics, Statistics or a related field.
• Be available to work full-time for 10-12 weeks (may depend on country specific internship requirements) during period of 1st June till 30th September.
• You are legally authorized to work permanently in both the European Union and countries in Europe.
• Solid understanding of natural language processing (NLP) concepts, including transformer-based models (e.g., BERT, GPT).
• Experience with data preprocessing techniques, including converting unstructured data (e.g., PDF/DOCX) into structured formats.
• Familiarity with deep learning frameworks such as TensorFlow or PyTorch for fine-tuning and deploying language models.
• Proficiency in Python, with experience in working with libraries for NLP, vector databases, and microservices development.
• Practical experience with version control systems like Git for collaborative development.
• Awareness of cloud-based solutions (e.g., AWS, Azure, or Google Cloud) for scalable model training and deployment is desirable.
• Excellent problem-solving skills and the ability to work independently and collaboratively in a team environment.
• Effective communication skills in English, both written and verbal.