Applied AI & Clinical Technology Innovation Intern
Genmab is an international biotechnology company dedicated to improving patient lives through innovative antibody therapeutics. The Applied AI & Clinical Technology Innovation Intern will support initiatives applying automation and AI to enhance clinical development operations.
Responsibilities
- Support the design, prototyping, or enhancement of AI- or automation-driven tools that improve workflows across clinical development
- Build or extend low-code solutions using the Microsoft Power Platform (Power Automate, Power Apps, Copilot Studio) to streamline manual processes
- Contribute to applied AI activities using platforms such as OpenAI, Anthropic, Replit, and internal DD&AI technologies
- Perform process mapping and requirement gathering with cross-functional partners to understand operational pain points and value opportunities
- Assist in evaluating new clinical technologies (e.g., CTMS enhancements, workflow orchestration tools) and support implementation activities as appropriate
- Participate in proof-of-concept development, including testing, documentation, iteration, and presenting findings to stakeholders
- Apply structured problem-solving and attention to GxP, security, and privacy considerations when designing prototypes
- Collaborate with mentors and multidisciplinary teams to deliver a tangible project outcome or final presentation demonstrating internship impact
Skills
- Enrollment in a Bachelor's or Master's program in Engineering, Computer Science, Data Science, Information Systems, Business Analytics, Biomedical Engineering, or a related technical/quantitative field
- Foundational experience in at least one of the following: programming (Python, JavaScript, or similar), low-code / automation tools (Microsoft Power Platform, UiPath, etc.), applied AI or data science coursework, full-stack developer or AWS cloud engineering
- Strong analytical, problem-solving, and conceptual thinking abilities
- Demonstrated interest in applying technology to improve real-world processes
- Skills at translating technical concepts for diverse audiences effectively
- Ability to work both independently and collaboratively within multidisciplinary teams
- High attention to detail, accountability, and commitment to quality—especially in regulated or data-sensitive environments
- Familiarity with generative AI concepts, prompt engineering, or LLM-powered workflows
- Experience with workflow automation, app building, or scripting in low-code environments
- Prior exposure to software development best practices (e.g., version control, documentation, modular code)
- Understanding of GxP, AI traceability and validation, data privacy, cybersecurity principles, or compliance-sensitive environments
- Experience with process improvement activities (Lean, Six Sigma, root-cause analysis)
- Ability to rapidly learn new technologies and apply them to ambiguous problem spaces
- Curiosity, creativity, and a proactive mindset to execute on digital innovation
Company Overview