Intern, Translational Data Science — Bayesian & Hierarchical

StudentJob; Utrecht; Ibrido; EUR 7600 - 9100; Tempo pieno

Vantaggi offerti da questo lavoro

Pension

Health insurance and wellness benefits

Paid time off

Employee support programs

Descrizione del lavoro

Genmab is seeking a highly motivated Master’s intern to join the Early Translational Data Science team in Utrecht, Netherlands. You will apply hierarchical and Bayesian methods to historical preclinical tumor data, exploring borrowing of control arms to reduce animal use while preserving statistical power.

This 9‑month internship starts February or March, is hybrid (three days on site, two remote), and provides multidisciplinary collaboration with scientists in NCS and PiP, with exposure to R or

Competenze

• Currently enrolled in a Dutch Master's degree program in Biostatistics, Bioinformatics, Biomedical Sciences, Data Science or related field.
• Strong statistical expertise demonstrated through coursework and research, including internships if possible.
• Proficiency in R and/or Python with clear, well-documented code.
• Affinity with biological data and familiarity with hierarchical or mixed-effects models.
• Excellent written and spoken English; ability to communicate complex findings clearly.

Mansioni

• Assemble and harmonize retrospective control and treatment data across tumor models and studies.
• Build reproducible analysis pipelines (R, notebooks) to visualize variance in control trajectories.
• Classify tumor models for historical control borrowing using cross-study variance and meta-regression.
• Fit and validate hierarchical Bayesian models on historical data, including leave-one-study-out backtesting.
• Simulate reduced control group sizes to generate defensible, model-specific sample-size recommendations.
• Collaborate cross-functionally with scientists in Non-Clinical Safety and in vivo pharmacology.

Conoscenze

Strong statistical expertise

R and/or Python proficiency

Affinity with biological data

Familiarity with mixed-effects/hierach

Bayesian modelling knowledge

English communication

Collaborative, cross-disciplinary

Formazione

Master's degree in Biostatistics or related field

Descrizione del lavoro

Genmab is seeking a highly motivated Master’s intern to join the Early Translational Data Science team in Utrecht, Netherlands. You will apply hierarchical and Bayesian methods to historical preclinical tumor data, exploring borrowing of control arms to reduce animal use while preserving statistical power.

This 9‑month internship starts February or March, is hybrid (three days on site, two remote), and provides multidisciplinary collaboration with scientists in NCS and PiP, with exposure to R or