SCIENTIST COMPUTATIONAL BIOLOGY

We're Hiring: Scientist Computational Biology!

We are seeking a motivated and detail-oriented Scientist in Computational Biology to join our dynamic team. The ideal candidate will possess a strong foundation in computational methods and biological data analysis to contribute to cutting-edge research and development projects.

Location: San Diego, CA

Work Mode: Work From Office

Role: Scientist Computational Biology

Pay Scale: $150, 708 – $188, 392 (Dependent on Experience)

What You'll Do

• Target Antigen Discovery: Lead efforts to identify and validate novel antigen targets for
  
  

radiopharmaceutical therapy in oncology through integration of multi-omics data, including

RNA sequencing, proteomics, and genomics.

• Bioinformatics Analysis: Design and implement novel analytical frameworks to process,
  
  

visualize and interpret high throughput sequencing and multiplex flow cytometry data from pre-

clinical experiments, Real-World cohorts and internal clinical trial data to validate

pharmacodynamics effects, confirm the mechanism of action, and enable patient enrichment

strategies.

• Collaboration: Work closely with computational biology colleagues, and engage with cross-
  
  

functional teams, including discovery, translational, and clinical scientists, to provide

bioinformatics expertise and guidance on experimental design.

• Interpretation of Results: Generate hypothesis based on the analyses and present findings
  
  

to both technical and non-technical stakeholders, providing actionable insights to inform

radiopharmaceutical discovery and enable data-driven decision-making.

• Oncology Expertise: Apply oncology expertise to understand the molecular mechanisms
  
  

underlying cancer and therapeutic resistance, particularly in relation to radiopharmaceutical

therapy.

What We’re Looking For

• PhD in Bioinformatics, Computational Biology, Cancer Biology, or a related field with 3+ of
  
  

relevant industry experience.

• Expertise in bioinformatics tools and software for RNA-seq, proteomics, and other omics
  
  

data analysis.

• Individual contributor role requiring strong background in -omic (DNA, RNA, epigenetic,
  
  

proteomic) data analysis, biological interpretation and large-scale data analysis, particularly in

oncology.

• Proficiency in programming languages such as Python, R, and/or Perl, and experience with
  
  

bioinformatics software and platforms.

• Strong experience in statistical modeling and/or machine learning approaches, such as
  
  

mixed-effects models, predictive modeling, etc. to represent biological concepts.

Ready to make an impact? Apply now and let’s grow together!