Job Details

Job Title: Scientist Computational Biology (Drug & Biological Research)

Location: San Diego, CA 92121 (Onsite)

Duration: 6 Months+ (with possibility of extension)



Pay Rate: $90.57/hr. on W2



Work Schedule: Monday Friday, Standard Business Hours



Position Summary:

We are seeking an experienced and motivated PhD-level Bioinformatics Scientist with a strong background in oncology and multi-omics analysis to lead target antigen discovery for radiopharmaceutical therapies. You will work with large-scale, multidimensional datasets from preclinical models, real-world evidence, and internal clinical trials to identify and validate novel therapeutic targets.

This is a 100% onsite role, offering the opportunity to collaborate directly with a cross-functional team of discovery scientists, translational biologists, and clinical researchers in a fast-paced and innovative environment.



Key Responsibilities:

• Target Antigen Discovery: Analyze multi-omics datasets (RNA-seq, proteomics, genomics) to discover and prioritize novel antigens for radiopharmaceutical oncology therapy.


• Bioinformatics Analysis: Design and implement analytical frameworks to interpret high-throughput sequencing and flow cytometry data; support PD biomarker discovery and patient enrichment strategies.


• Collaborative Research: Work closely with discovery, translational, and clinical teams to guide experimental design and translate bioinformatic insights into therapeutic strategies.


• Scientific Communication: Generate testable hypotheses, interpret results, and clearly present findings to both technical and non-technical stakeholders.


• Oncology Expertise: Apply deep understanding of cancer biology and resistance mechanisms, particularly related to targeted and radiopharmaceutical therapies.

• PhD in Bioinformatics, Computational Biology, Cancer Biology, or a related field.


• 3+ years of relevant postdoctoral or industry experience in bioinformatics or computational oncology.


• Proven expertise in analysis of RNA-seq, proteomics, DNA/epigenomics, and other multi-omics data.


• Proficiency in Python, R, and/or Perl for data analysis.


• Solid foundation in statistical modeling, including linear/mixed-effects models and predictive analytics.


• Strong communication skills, with the ability to present complex data to diverse scientific audiences.


• Demonstrated track record of impactful research (e.g., peer-reviewed publications, internal project leadership).

• Experience in immune-oncology and/or radiopharmaceutical therapy.


• Familiarity with cloud-based computing environments (e.g., AWS, Google Cloud).


• Experience with clinical data analysis, including SDTM/ADaM datasets and biomarker strategies.


• Working knowledge of machine learning applications in omics-based biomarker discovery.