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PhD Scientist - Statistical Analysis - Galway

  • Sector: Science & Pharma
  • Contact Email:
  • Job Ref: 22626

Excellent opportunity for a PhD Scientist with a focus on Statistical Analysis working for a global Medical Devices leader in Galway. The ideal person would have PhD focus Computational, Chemical, or Structural Biology or related disciplines, or a Bachelor's Degree / Master's Degree in the same disciplines with 2+ years of research experience. The ideal candidate will be proficient in Python and significant experience with relevant macromolecular modelling software (i.e. PyRosetta, AlphaFold, MOE, Schrödinger).

Overview of your responsibilities (full job description available on request):

  • Develop structural/computational biology workflows and machine learning methods for analysing and designing biomolecular structures.

  • Engineer key attributes of diagnostic antibodies/antigens and conduct epitope mapping for optimal design and selection.

  • Stay updated on advancements in the field, transferring critical technologies for high-throughput antibody screening.

  • Collaborate with interdisciplinary teams and commercial partners.

  • Analyze and interpret data for the scientific and leadership team.

  • Drive ongoing innovation by introducing latest trends in machine learning and computational protein design.

Knowledge, Skills and Experience Required for the Role:

  • PhD in Computational, Chemical, or Structural Biology or related fields, or BS/MS with 2+ years of research experience.

  • Experience in applying advanced machine learning and computational methods for peptide and protein design.

  • Strong computational and sequence analysis skills.

  • Proficiency in Python and experience with relevant macromolecular modeling software.

  • Understanding of antibody structure and function.

  • Success in developing, optimising, and troubleshooting protein/antibody characterisation techniques.

For a confidential discussion and more information on the role contact Courtney Russell

+353 (0) 71 9108062