Computational Biologist

OncoHost is a precision oncology company that combines proteomic analysis with advanced computational models to optimize therapeutic strategies. We develop liquid biopsy-based diagnostic tools to predict treatment efficacy and toxicity in cancer patients and identify potential mechanisms of treatment resistance.

Purpose

A Computational Biologist conducts research by integrating computational analyses with biological reasoning. This role reports to OncoHost’s Director of Science and Innovation.

Duties and Responsibilities

• Perform bioinformatic analyses on omic and clinical data

• Derive biological insights from omics data
• Drive hypothesis generation by applying computational biology approaches, integrating data, and incorporating biological knowledge
• Develop new predictive tools using computational biology to transform omics data into meaningful biological insights
• Apply basic statistics (e.g., parametric and non-parametric tests, p-values, correlation metrics, PCA) and good experimental practices (e.g., examination of batch effects and confounding factors)

• Collaborate with research groups and contribute to publications in peer-reviewed journals

• Support intellectual property (IP) applications

Qualifications/Requirements

• Ph.D. in Computational Biology or Bioinformatics; additional background in biology is a big advantage
• Demonstrated expertise in Python, including data visualization capabilities
• Proven experience in transcriptomics, proteomics, and/or metabolomics data analysis. Skills in additional fields are a plus
• At least 2 years of relevant industry experience
• Extensive background in cancer biology research
• Experience in independent scientific research
• Team player with the ability to explain complex topics to individuals from other disciplines
• Excellent ability to manage multiple projects simultaneously
• Passionate, motivated, and curious
• Independent and fast learner
• Strong critical thinking skills

Working Conditions

5 days per week: 4 working days per week from the office, 1 day working remotely.