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Paid Internship
Work Mode
Time Spent
Required Degree
Duration

6Open Positions

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  • Intern, Discovery Data Science (Project: proteomics data integration)

    Genmab
    Utrecht, Netherlands
    Found 1 month ago
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Intern, Discovery Data Science (Project: proteomics data integration)

Genmab
Found 1 month ago
Location
Utrecht, Netherlands
Duration (Months)
8.5 Months
Time
Full-time
Work Mode
Hybrid
Salary
Not disclosed
Visa Help
Not disclosed
Last Verified
1 month ago

Education

  • Master

Skills & Qualifications

Technical Skills

  • R
  • Python
  • machine learning
  • data analysis
  • algorithm development
  • mass spectrometry data analysis
  • proteomics data analysis

Soft Skills

  • Motivated
  • Strong interest
  • Foundational knowledge
  • Strong interest in learning
  • Enjoy working collaboratively
  • multidisciplinary team
  • genuine passion
  • precision and excellence
  • rooted-in-science approach
  • generous collaborator
  • work in teams
  • broad spectrum of backgrounds
  • pride in enabling the best work of others
  • grapple with the unknown
  • innovative
  • work hard
  • have a little fun

Job Description

As our newest student addition, you will join our Discovery Data Science team to strengthen proteomics-driven therapeutic target discovery in oncology. Mass-spectrometry (MS)–based proteomics provides valuable insights into tumor-specific protein expression, but datasets are often affected by missing values, batch effects, and inter-study variability. In this project, you will develop and evaluate statistical and machine learning approaches for mechanism-aware imputation and cohort integration, enabling more robust and interpretable protein-level analyses across studies. You will gain hands-on experience in high-dimensional omics data analysis and see how computational insights directly inform innovative antibody therapeutic strategies in oncology! The main research aim of this project is to establish a robust computational foundation for proteomics-driven therapeutic target identification, ensuring that protein-level evidence can be integrated, interpreted, and leveraged with maximal precision in oncology research.

Requirements

  • Motivated student enrolled in a Master’s program in Computer Science, Biomedical Sciences, Bioinformatics, or a related field at an HBO/University in the Netherlands.
  • Experience with R and/or Python programming.
  • Strong interest in machine learning, data analysis, and algorithm development.
  • Foundational knowledge of cancer biology and/or immunology.
  • Experience in, or a strong interest in learning, proteomics data analysis and antibody drug discovery.
  • Enjoy working collaboratively in a multidisciplinary team.

Related Field

  • AI & Machine Learning

Related Subfield

  • Applied Machine Learning

Languages

  • English

Nice to Haves

  • Cancer biology
  • Immunology
  • Proteomics data analysis
  • Antibody drug discovery
  • Experience working in a fast-growing, dynamic company
▶Apply Now

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