Associate Principal Scientist, Biomarker Discovery, Multiomics

Merck Merck · Pharma · MA

Seeking a scientist with expertise in multi-omics and single-cell technologies for biomarker discovery in immunology drug discovery. The role involves designing and executing laboratory experiments, collaborating with computational scientists and AIML data scientists, and evaluating emerging technologies. Requires a PhD and hands-on experience with various genomic and spatial multiomics assays, as well as computational analysis of related datasets.

What you'd actually do

  1. Design and execute hands-on laboratory experiments for large-scale studies across single cell and spatial multiomics assays, including single cell RNA-seq, REAP-seq/CITE-seq, CROP-seq/Perturb-seq, immune profiling, Multiome ATAC-seq, and spatial multiomics platforms such as CosMx, Xenium, COMET mIF, and Digital Pathology.
  2. Support and develop perturbation, cell-culture, and tissue-based profiling studies to enable mechanistic studies and translationally relevant biological investigations.
  3. Collaborate closely with experimental biologists, automation engineers, computational scientists, data analysts, AIML data scientists, and therapeutic area subject matter experts to address biological questions, develop experimental strategies, and execute project plans.
  4. Independently drive projects from study design through execution, data interpretation, troubleshooting, and communication of results to stakeholders and senior leadership.
  5. Evaluate, implement, and scale emerging single cell and spatial technologies, computational approaches, and biological models for use in early discovery and translational research.

Skills

Required

  • Demonstrated application of single cell and/or spatial multiomics to Immunology.
  • Extensive hands-on expertise in molecular biology assays and high-throughput genomic technologies, particularly single cell RNA-seq, REAP-seq/CITE-seq, CROP-seq/Perturb-seq, and/or spatial transcriptomics.
  • Demonstrated ability to work across both single-cell and spatial workflows, with enough breadth to contribute outside a narrow technical specialty.
  • Experience with perturbation, cell and/or tissue based systems, and the ability to connect assay design to biological and translational questions.
  • Proven experience with advanced profiling technologies such as 10x Genomics scRNAseq/STx, Bruker STx/mIF/MSI, Parse scRNAseq or related platforms, including demonstrated execution of these assays at scale.
  • Proficiency in using automation tools for high throughput sample processing and data execution, such as Biomek, Hamilton, Leica Bond Rx, or equivalent systems.
  • Experience using Linux/Unix OS and high-performance compute (HPC) environments.
  • Expertise in R and/or Python.
  • Demonstrated experience in computational analysis and biological interpretation of single cell RNA-seq, Spatial Tx, mIF and/or related multimodal datasets.
  • Experience partnering with cross-functional groups including experimental biologists, data scientists, TA biologists and IT Engineering
  • Strong understanding of experimental design, scientific rigor, troubleshooting, and documentation, with the ability to independently lead studies.
  • Exceptional problem-solving abilities, critical thinking skills, and analytical expertise.
  • Excellent communication skills, both written and verbal, with the ability to convey complex technical information to a wide range of audiences and excel working as “One Team” across departments and cross-functional teams.

Nice to have

  • Experience operating effectively in a matrixed team structure with alignment to therapeutic area priorities and collaboration across technical leads.
  • Broad scientific versatility and learning agility, with the ability to expand into adjacent workflows or biological domains as project needs evolve.
  • A strong publication history in reputable peer-reviewed journals.

What the JD emphasized

  • AIML data scientists
  • computational scientists
  • computational analysis