Postdoctoral Fellow-MSH-30030-295

About the Role

The Palacios Laboratory at the Icahn School of Medicine at Mount Sinai is seeking an exceptional Senior Postdoctoral Fellow to provide scientific and operational leadership for a cross-program computational biology unit within the laboratory. The candidate will supervise and mentor master's-level bioinformaticians, establish shared analytical standards, and partner with experimental investigators across multiple research programs at the intersection of virology, genomics and immunology. We conduct interdisciplinary research in viral genomics, emerging infectious diseases, host–pathogen interactions, pathogen discovery, and medical countermeasure development. The fellow will work within a collaborative research environment at the Icahn School of Medicine at Mount Sinai and will interact with investigators across disciplines and translational research.

Position Overview

The position integrates three complementary areas of leadership:

• Computational discovery and scientific leadership: Develop a cohesive computational strategy that connects complex biological data with experimental discovery. The fellow will identify high-value questions, create analytical approaches that generate testable hypotheses, and lead a team capable of advancing multiple ambitious research efforts.
• Agentic AI as an emerging scientific capability: Working with the PI, the fellow will have substantial intellectual ownership in defining and developing the laboratory's agentic-AI approach to biological research. This includes creating systems that extend how scientists interrogate data, connect evidence, design analyses, and move from observation to experimentally actionable insight.
• Integrative computational biology: Bring genomics, multi-omics, structural biology, immunology, and predictive modeling together to reveal mechanisms of host-pathogen interaction and guide the design of vaccines, therapeutics, and other interventions. By working closely with experimental scientists, the fellow will ensure that computation shapes the questions, experiments, and decisions that determine program success. The fellow will lead work from study design through publication and program milestones.

Responsibilities

Computational Unit Leadership and Program Support

• Lead, mentor, and coordinate master's-level bioinformaticians supporting multiple laboratory programs; establish clear ownership, priorities, timelines, and quality expectations.
• Partner with investigators, experimental scientists, program managers, and collaborators to convert biological questions and milestones into feasible computational work plans.
• Review code, statistical methods, results, and interpretations; provide technical escalation and ensure conclusions are defensible.
• Establish unit practices for intake, prioritization, code review, testing, documentation, data stewardship, and reproducible delivery.
• Build team capability through mentoring, technical training, standardized documentation, and feedback.

Agentic AI and Biological Pipeline Engineering

• Architect agentic-AI systems that orchestrate approved tools for data intake, quality control, workflow selection, analysis, visualization, reporting, and knowledge capture.
• Develop specialized agents and tool interfaces for viral and functional genomics, multi-omics, single-cell and spatial analysis, structural bioinformatics, immunological modeling, and experimental prioritization.
• Implement human approvals, role-based permissions, audit trails, provenance, structured outputs, uncertainty reporting, and safeguards for controlled data.
• Create benchmarks for accuracy, reproducibility, robustness, hallucination and failure detection, efficiency, and scientific utility.
• Integrate agents with version-controlled workflows, containers, HPC or cloud resources, metadata systems, and laboratory data platforms.

Cross-Program Computational Biology

• Lead viral genomic and metagenomic analyses, including assembly, variants, comparative genomics, phylogenetics, pathogen discovery, surveillance, and evolution.
• Integrate functional screens with transcriptomic, proteomic, interactomic, phenotypic, and virological data to identify virus-host dependencies.
• Analyze single-cell, single-cell spatial, serological, flow cytometry, and protection datasets across longitudinal scales to characterize immune states and model vaccine immunogenicity and durability.
• Support receptor/interface modeling, human-variation analysis in the context of drug-targeting, followed by edit ranking, on/off-target assessment, and analysis of antiviral efficacy versus host function.
• Apply workflow-management and containerization approaches to support computational reproducibility.
• Maintain organized analytical records, data dictionaries, software documentation, and versioned outputs.
• Build documented and version-controlled analytical workflows suitable for reuse across projects and collaborators.
• Produce publication-quality visualizations, technical reports, and clear summaries for both computational and experimental audiences.
• Contribute to peer-reviewed manuscripts and research proposals.
• Present findings at laboratory meetings, program reviews, scientific conferences, and meetings with external collaborators or sponsors.

Qualifications

• Ph.D. or equivalent degree in computational biology, bioinformatics, machine learning, quantitative biology, computer science, biomedical engineering, virology/genomics, or a related discipline.
• A record of increasingly independent computational research and scientific productivity appropriate for a senior postdoctoral appointment.
• Experience leading projects and mentoring or supervising computational scientists, analysts, trainees, or software contributors.
• Advanced Python and working R proficiency, strong software-engineering practices, and the ability to review production-quality analytical code.
• Strong foundation in statistics, experimental design, high-dimensional biological data analysis, and biological interpretation.
• Experience with Linux/Unix, high-performance or cloud computing, workflow management, version control, automated testing, and containerization.
• Excellent communication, organization, and interpersonal skills, including management of concurrent multidisciplinary projects.

Preferred Skills

Candidates are not expected to have experience in every area listed below. Competitive applicants will demonstrate substantial expertise in one or more areas and a clear ability to learn complementary methods.

• Experience analyzing single-cell RNA-seq data using frameworks such as Seurat, Scanpy, Bioconductor, or comparable tools.
• Experience with spatial transcriptomic or spatial proteomic data, including image-associated or coordinate-resolved molecular measurements.
• Experience integrating transcriptomic, proteomic, immunological, imaging, or clinical datasets.
• Experience developing and rigorously evaluating machine-learning models for biological or biomedical applications.
• Experience with viral genomics, phylogenetics, molecular evolution, metagenomics, pathogen discovery, or genomic epidemiology.
• Knowledge of immunology, vaccinology, host–pathogen interactions, respiratory viruses, or emerging infectious diseases.
• Familiarity with workflow systems such as Nextflow, Snakemake, or Workflow Description Language.
• Familiarity with Git, Docker, Apptainer/Singularity, package development, automated testing, and research-software documentation.
• Experience working with large collaborative or multi-institutional research programs.
• Experience contributing to grant applications, technical reports, or milestone-driven research programs.

Pay

Salary: $74,692

Department: Microbiology
Physical work location: 1468 Madison Avenue, New York, New York 10029
PI/Supervisor: Gustavo Palacios, PhD
Lab: https://palacioslab.com/
Department: https://icahn.mssm.edu/about/departments/microbiology
Administrative Contact: Molly Deroy, molly.deroy@mssm.edu