Senior Research Scientist, Translational Medicine – Multiple Myeloma / Immuno-Oncology

Arbeitsbeschreibung

Summary

The Senior Scientist will design and execute multi-omics biomarker analyses pertinent to multiple myeloma and other heme-oncology indications.

As a member of the Translational Medicine team, you will be at the intersection of Research and Clinical Development, providing valuable insight into the function and safety of CAR-T cells, the investigation of mechanisms of action, response, relapse and toxicity and the development of potential prognostic and predictive tools, supporting pipeline advancement and informing design of next generation therapeutics and clinical development of Kite’s chimeric antigen receptor (CAR-T) programs.

Essential requirements are a solid understanding of cancer biology and immune therapy, a strong understanding and expertise with multi-omics analytical methods (eg scRNA-seq, Proteomics, Metabolomics, flow cytometry, Spatial transcriptomics) and downstream computational data processing, data interpretation and reporting, demonstrated by education, previous professional experience and authorship in high-impact scientific communications/publications. Familiarity with cloud computing platforms such as AWS and/or high-performance computing (HPC) environments is preferred.

Key Responsibilities:

• Collaborates with analytical teams within translational medicine and cross-functionally for planning and execution of correlative studies around disease biology, drug mechanisms of action and mechanisms of response, relapse, and toxicity.
• Oversees, directs, and establishes the computational analytical workflows.
• Writes, reviews, leads and/or contributes to research reports, and all project-related documents, as needed.
• Contributes and leads internal and external scientific presentation, discussions/collaborations, and publications, and engages with key internal stakeholders.
• Leverages cloud based or HPC infrastructure for scalable processing of large-scale multi-omics datasets.

Basic / Essential Qualifications

Bachelor's Degree and 8+ years of scientific experience

OR

Master's Degree and 6+ years of scientific experience

• Strong background in cancer biology and immuno-oncology and/or immunology (or closely related field)
• Strong understanding of clinical, translational, and mechanistic data
• Strong expertise in analysis of large multi-omics datasets, including proteomics, transcriptomics and other genomic analyses (eg scRNAseq, WES, ATACseq), using computational methods (eg R programing, Python) and Machine Learning to profile disease biology and immune cell repertoire.
• Strong collaboration, excellent interpersonal and communication skills
• Proficient with data presentations to communicate to a diverse cross-functional audience.
• Maintain a high degree of accuracy and attention to details.

Preferred Qualifications:

• Ph.D. degree in Immuno-oncology-related field (cancer biology, immunology, bioinformatics or a closely related field)
• Experience with cloud-based data storage, pipeline deployment, and computation using platforms such as AWS or HPC etc.
• Experience working with engineered T cells
• Understanding of early and/or late-stage drug and translational development process; including prior clinical trial experience in industry or academia
• Direct experience and/or in depth understanding of an array of analytical methods such as NGS methods, flow cytometry, ELISA or other ligand-based immune-assay, IHC/IF, dd-PCR, FISH.
• Comfortable in a matrixed and fast-paced company environment and able to adapt to changing priorities
• Understanding of clinical landscape, evolving therapy, competitive scenarios in the immune-oncology space
• Hands-on experience analyzing proteomics and/or metabolomics data sets is preferred.
• Familiarity with workflow management systems (e.g., Nextflow, Snakemake) and reproducible analysis tools (e.g., Docker, GitHub)