Frontier Research Mission
I build genomic analysis workflows that connect molecular mechanisms to disease biology. My work spans developmental pathways, transcriptomics, clinical datasets, and scalable computational systems for turning high-dimensional biological data into interpretable results.
I am especially interested in how molecular programs regulate tissues across biological timepoints, and how those patterns can clarify disease processes from dementia to cancer. The work calls for pragmatic data integration, statistical modeling, machine learning, and production-ready scientific software.
Expertise
Python · R · SQL · Data science · Cloud/HPC workflows · Statistics and machine learning
Experience Highlights
- Built reproducible genomic workflows for large-scale sequencing and transcriptomic datasets.
- Integrated molecular and clinical data to support translational disease research.
- Developed scientific software and analysis pipelines across cloud, HPC, and containerized environments.
Programming Languages
Python, R, SQL
Data Science
Pandas, NumPy, scikit-learn, PyTorch, Matplotlib, ggplot2, Bioconductor, R Shiny
Computational Resources
High-performance cluster, AWS (S3, EC2, Batch, Lambda), Google Cloud Compute, Kubernetes, Docker, Argo, WDL, Nextflow, Prefect, DNAnexus, Git, JIRA, SQL (MySQL, Spark), noSQL (MongoDB, DynamoDB), Neo4j
Statistics and Machine Learning
Hypothesis testing, linear and generalized linear modeling, multivariate modeling, clustering, dimensionality reduction, supervised and unsupervised classification, random forests, HMM, Kaplan-Meier
Contact
Available for bioinformatics consulting, genomic data strategy, translational research collaborations, and scientific software projects.
For collaborations, consulting, or scientific data questions, email tfriedrich.solutions@gmail.com.
Older Writing & Projects
Earlier scientific writing, research, and project links.