Eric Vornholt, PhD

Eric Vornholt, PhD

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Data Scientist | Computational Biologist | Biostatistician
New York, United States
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Starting at USD130k/year

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Résumé

Jobs verified_user 0% verified
  • Pfizer
    Omics Data Scientist
    Pfizer
    Aug 2025 - Current (1 year)
    Performed external systems vaccinology dataset ingestion, harmonization, and integration for internal analysis.
  • Icahn school of medicine at mount sinai
    Assistant Professor
    Icahn school of medicine at mount sinai
    Jan 2024 - Jul 2025 (1 year 7 months)
    Assistant Professor Project: Predictive Modeling of Molecular Variation in Brain Tissue • Designed and implemented a predictive scoring system using machine learning (elastic net regression) to classify brain samples based on gene expression, with model performance optimized through cross-validation. • Evaluated the utility of predicted probabilities to replicate and account for biological variation in linear mixed models. • Developed a custom R pipeline to automate the training, testing, and validation of predictive metrics, tested on 10 datasets comprising 1.5 million cells to ensure reliability and scalability. • Integrated Google Cloud Storage (GCS) to securely manage and archive large-scale genomic datasets, ensuring high availability
  • Icahn school of medicine at mount sinai
    Postdoctoral Fellowship
    Icahn school of medicine at mount sinai
    Dec 2020 - Jan 2024 (3 years 2 months)
    Job title: Postdoctoral Fellowship Job description: Project: Comprehensive Analysis of Brain States Using Single-Cell Genomic Data • Organized, cleaned, and processed single-cell genomic datasets spanning ~500,000 cells, ensuring data quality and readiness for downstream analysis. • Applied unsupervised learning techniques, including clustering algorithms and dimensionality reduction methods (e.g., t-SNE, UMAP), to identify and annotate distinct cell types based on over 30,000 features. • Analyzed and interpreted significant patterns of association, translating high-dimensional data into meaningful insights about biological variation and trends. • Leveraged Google Cloud Storage (GCS) to manage and secure extensive genomic datasets, ensuring
  • Virginia Commonwealth University
    Graduate Teaching Assistant
    Virginia Commonwealth University
    Aug 2017 - Jun 2019 (1 year 11 months)
    Course: Genetics Laboratory (BIOZ 310)
  • Virginia Commonwealth University
    Graduate Research Assistant
    Virginia Commonwealth University
    Aug 2016 - Dec 2020 (4 years 5 months)
    Project: Functional Genomic Analysis of Postmortem Brain Tissue in Alcohol Abuse • Constructed hierarchical networks using unsupervised learning techniques to analyze relationships in complex datasets, uncovering structured patterns linked to alcohol use disorder in the brain. • Investigated imputed genetic data and its association with measured variation to uncover predicted functional relationships within complex datasets. • Integrated heterogeneous molecular data by correlating summary statistics between distinct datasets to identify significant interactions.
  • U
    Undergraduate Research Assistant
    University of Arizona Department of Psychology
    Jan 2014 - Dec 2015 (2 years)
    Research Topic: Naturalistic observation of social interactions and quantitative text analysis of natural l language use. Primary Advisor: Matthias Mehl, Ph.D.
  • U
    Undergraduate Research Assistant
    University of Arizona Department of Ecology and Evolutionary Biology
    Jan 2014 - Dec 2015 (2 years)
    Research Topic: Transcriptomic analysis of toxic vs. non-toxic algal strains within the same species. Primary Advisor: Jerimiah Hackett, Ph.D.
Education verified_user 0% verified
  • Virginia Commonwealth University
    Doctor of Philosophy - PhD, Behavioral and Statistical Genetics
    Virginia Commonwealth University
    Jan 2016 - Dec 2020 (5 years)
    Research Interests: Gene expression, epigenetics, addiction, DNA methylation/hydroxymethylation, neurodevelopment, synaptic plasticity, neuropsychiatric etiology, postmortem brain and hiPSCs.
  • University of Arizona
    Bachelor of Science - BS, PSYCHOLOGY
    University of Arizona
    Jan 2013 - Dec 2015 (3 years)
    Included interdisciplinary coursework spanning molecular biology, genetics, and psychology.
Projects (professional or personal) verified_user 0% verified
  • Icahn school of medicine at mount sinai
    Functional Genomic Analysis of Postmortem Brain Tissue in Alcohol Abuse
    Icahn school of medicine at mount sinai
    Jan 2021 - May 2025 (4 years 5 months)
    • Constructed hierarchical networks using unsupervised learning techniques to analyze relationships in complex datasets, uncovering structured patterns linked to alcohol use disorder in the brain. • Investigated imputed genetic data and its association with measured variation to uncover predicted functional relationships within complex datasets. • Integrated heterogeneous molecular data by correlating summary statistics between distinct datasets to identify significant interactions.
  • C
    Comprehensive Analysis of Brain States Using Single-Cell Genomic Data
    Jan 2021 - May 2025 (4 years 5 months)
    • Organized, cleaned, and processed single-cell genomic datasets spanning ~500,000 cells, ensuring data quality and readiness for downstream analysis. • Applied unsupervised learning techniques, including clustering algorithms and dimensionality reduction methods (e.g., t-SNE, UMAP), to identify and annotate distinct cell types based on over 30,000 features. • Analyzed and interpreted significant patterns of association, translating high-dimensional data into meaningful insights about biological variation and trends.
  • Icahn school of medicine at mount sinai
    Predictive Modeling of Molecular Variation in Brain Tissue
    Icahn school of medicine at mount sinai
    Jan 2021 - May 2025 (4 years 5 months)
    • Designed and implemented a predictive scoring system using machine learning (elastic net regression) to classify brain samples based on gene expression, with model performance optimized through cross-validation. • Evaluated the utility of predicted probabilities to replicate and account for biological variation in linear mixed models. • Developed a custom R pipeline to automate the training, testing, and validation of predictive metrics, tested on 10 datasets comprising 1.5 million cells to ensure reliability and scalability. • Integrated PostgreSQL as a database management solution to organize and store complex biological datasets, ensuring efficient data retrieval and structural integrity throughout the computational research project.
Publications verified_user 0% verified
  • N
    Divergent landscapes of A-to-I editing in postmortem and living human brain
    Nature Communications
    Jun 2024
  • M
    Characterizing cell type specific transcriptional differences between the living and postmortem human brain.
    MEDRXIV
    May 2024
  • M
    Multiomic foundations of human prefrontal cortex tissue function
    MEDRXIV
    May 2024
  • M
    A study of gene expression in the living human brain
    MEDRXIV
    Apr 2023
  • A
    Identifying a novel biological mechanism for alcohol addiction associated with circRNA networks acting as potential miRN
    Addiction Biology
    Nov 2021
  • PLOS ONE
    Network preservation reveals shared and unique biological processes associated with chronic alcohol abuse in NAc and PFC
    PLOS ONE
    Dec 2020
  • A
    Assessing the role of long noncoding RNA in nucleus accumbens in subjects with alcohol dependence
    Alcoholism Clinical and Experimental Research
    Dec 2020
  • N
    Postmortem brain tissue as an underutilized resource to study the molecular pathology of neuropsychiatric disorders acro
    Neuroscience Biobehavioral Reviews
    Jan 2019