AI Lab Intern at Genmab in Princeton

Summary: Genmab is an international biotechnology company dedicated to improving patients' lives through innovative antibody therapeutics. The AI Lab Intern will contribute to a defined summer project, supporting broader experimentation across Genmab’s AI and data initiatives while working alongside AI engineers and data scientists. Responsibilities: - Build, test, and refine AI or machine learning prototypes that address real research, operational, or knowledge-workflow problems - Translate ambiguous questions into structured experiments, measurable success criteria, and clear technical recommendations - Write high-quality Python code for data preparation, model experimentation, evaluation, and lightweight application development - Partner with AI engineers, scientists, and cross-functional stakeholders to gather requirements, validate assumptions, and present results - Contribute to experiments involving modern AI techniques such as LLM applications, retrieval systems, agentic workflows, multimodal inputs, or predictive models, depending on project needs - Document methods, findings, and tradeoffs in a form that teammates can reuse after the internship ends - Apply sound engineering practices around reproducibility, data handling, responsible AI use, and privacy Required Qualifications: - Currently enrolled in a bachelor's or master's program in computer science, data science, machine learning, bioinformatics, computational biology, statistics, applied mathematics, biomedical engineering, or a related field - Expected academic standing for Summer 2026: rising junior, rising senior, or current master's student - Coursework, research, or project experience in machine learning, deep learning, natural language processing, data analysis, or software engineering - Working proficiency in Python and familiarity with common ML tools or libraries such as pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Git, or Jupyter - Strong analytical thinking, curiosity, and the ability to communicate clearly with both technical and non-technical collaborators - Interest in applying AI to healthcare, biotechnology, or other real-world scientific problems Preferred Qualifications: - Exposure to large language models, prompt engineering, retrieval-augmented generation, evaluation frameworks, or AI agents - Experience working with biological, clinical, chemistry, or other scientific datasets - Familiarity with cloud environments, APIs, version control workflows, or building small internal tools for end users - Prior internship, lab, hackathon, or open-source experience that demonstrates initiative and ownership Required Skills: Machine Learning, Deep Learning, Python Important Skills: Natural Language Processing, Data Analysis, Software Engineering Nice-to-Have Skills: Analytical Thinking, Curiosity