Merck
Cambridge (320 Bent Street), MA
Shift: Full time
Job Description We are seeking a dedicated and highly motivated automation engineer/scientist to join the Data, AI Genome Sciences (DAGS) group at our Research Laboratories in Cambridge, MA. The successful candidate will focus on the development, implementation, operation, and optimization of automated systems and associated instrumentation supporting single-cell, spatial, and molecular omics workflows, with particular impact in Immunology Biomarker Discovery. This individual will join the Spatial and Single Cell Multiomics (SSM) Team within DAGS, a creative and highly collaborative group that leverages cutting-edge automation and advanced multiomics technologies to drive Biomarker Discovery and innovation across the drug development pipeline, from pre-clinical to clinical stages. Our team applies Spatial Multiomics platforms including CosMx WTx, Xenium, COMET mIF, Digital Pathology, and MSI as multi-omics single-cell approaches including REAP-seq/CITE-seq, CROP-seq/Perturb-seq, immune profiling, and Multiome ATAC-seq. SSM collaborates closely with therapeutic areas including Oncology, Immunology, Neuroscience, and Cardiometabolic Disease, as partner functions across Data, AI Genome Sciences, Data Science Scientific Informatics, Quantitative Bioscience, and ChemBio within the Discovery, Preclinical and Translational Medicine (DPTM) organization. Key Responsibilities Collaborate closely with experimental biologists, automation engineers, data scientists, and therapeutic area subject matter experts to develop and implement scalable automation workflows that enable high-quality, reproducible data generation in a timely manner. Develop, implement, optimize, and validate automated workflows for single-cell, spatial, and molecular omics assays, including Parse-seq, 10x Flex, CROP-seq/Perturb-seq, immune profiling, Multiome ATAC-seq, spatial workflows, Olink HT, high-throughput CRISPR screens, and complex cell-based model systems. Integrate instrumentation, process controls, and QC metrics into automated workflows to improve robustness, reduce variability, and enable scalable laboratory operations. Monitor automated systems during workflow execution and perform system- and instrument-level troubleshooting, coordinate maintenance, and drive error recovery as needed. Support technology transfer, workflow scale-up, and deployment of new automated methods into routine laboratory operations. Prepare, document, and maintain automation methods, workflow parameters, SOPs, and experimental records to support reproducibility, compliance, and operational rigor. Partner proactively with cross-functional teams across DAGS, Therapeutic Areas, and RaDS-IT to accelerate impact on biomarker discovery and early drug discovery efforts. Clearly communicate workflow designs, protocols, performance metrics, and experimental results through presentations, technical documentation, and reports to stakeholders and senior leadership. Required Education Ph.D. in engineering, molecular biology, cell biology, genomics, computational biology or a related STEM discipline, with 3–5 years of post-graduate industry experience. Required Skills and Experience Strong experience developing, implementing, and supporting automated workflows for single-cell, spatial, and/or multi-omics assays. Experience with automated systems and associated instrumentation used in omics workflow execution. Experience supporting technology transfer, assay scale-up, and deployment of new automated workflows into routine laboratory operations. Experience driving workflow standardization, operational excellence, and continuous improvement initiatives. Experience integrating instrumentation, process controls, assay monitoring, and quality control metrics into automated laboratory workflows. Strong experience troubleshooting automated workflows, monitoring instrument performance, and managing error recovery during execution. Strong understanding of experimental design principles, with excellent organizational and documentation skills, including preparation of SOPs, protocols, and technical summaries. Demonstrated problem-solving ability, critical thinking, and analytical skills. Excellent written and verbal communication skills, with the ability to train and mentor scientists with levels of experience. Ability to manage multiple projects simultaneously in a fast-paced, highly collaborative, matrixed environment. Experience working in Linux/Unix environments and high-performance computing (HPC) clusters. Preferred Skills and Experience Experience applying automation to biomarker discovery, translational research, and/or Immunology and Oncology research settings. Experience with automation platforms, scripting, or workflow control tools relevant to high-throughput biology laboratories. Fluency in scripting and data visualization tools such as Basic HSL, R, R Shiny, Python, and/or MATLAB. Familiarity with matrixed collaboration across functional areas including therapeutic areas,