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Postdoctoral Researcher (Spatial Multi-Omics)

70 000 - 92 666$
Формат работы
onsite
Тип работы
fulltime
Грейд
junior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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TL;DR
Postdoctoral Researcher (Spatial Multi-Omics): Leading computational analysis of spatial multi-omics data from multiple myeloma patient cohorts with an accent on spatial transcriptomics, single-cell spatial proteomics, digital pathology, and genomic integration. Focus on developing statistical models and novel analysis methods, predicting tumor outcomes and therapy response, and translating complex findings for cancer research.

Location: Cambridge, MA, United States; on-site

Salary: $70,000–$92,666.67 per year

Company

hirify.global and Massachusetts General Hospital conduct interdisciplinary cancer genome research integrating computational and wet-lab approaches.

What you will do

  • Lead computational analysis strategies for projects studying disease initiation, progression, and relapse in multiple myeloma.
  • Analyze spatial multi-omics data from multiple myeloma patient cohorts, including spatial transcriptomics, single-cell spatial proteomics, and digital pathology.
  • Define scientific questions and develop computational methods for integrating spatial and genomic data.
  • Design, implement, and test statistical models for predicting tumor outcomes, subtypes, molecular mechanisms, and therapy response.
  • Present findings to computational and non-computational audiences and prepare manuscripts, grants, patents, reports, and presentations.
  • Teach and mentor junior team members when appropriate.

Requirements

  • PhD in bioinformatics, computer science, machine learning, engineering, mathematics, statistics, physics, or a related quantitative discipline.
  • 0–1+ years of post-graduate experience.
  • Experience with computational analysis, algorithm development, statistics, and rigorous reproducible research.
  • Hands-on experience analyzing spatial multi-omic data is required.
  • Familiarity with single-cell RNA sequencing, immune BCR/TCR sequencing, and bulk and single-cell whole-genome sequencing.
  • Proficiency in at least one modern programming language; Python, R, or Matlab experience is preferred.

Nice to have

  • Experience analyzing data from emerging technologies.
  • Background in machine learning, biology, or cancer genomics.

Culture & Benefits

  • Collaborative environment with scientists, engineers, clinicians, and wet-lab researchers.
  • Mentoring, peer support, educational programs, journal clubs, conferences, and skill-building opportunities.
  • Medical, dental, vision, life, and disability insurance.
  • 401(k), flexible spending and health savings accounts, paid holidays, winter closure, paid time off, and parental and family care leave.

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