Muhammad Usman
Research Assistant
Experience
Research Assistant
Saarland University
- Applied AI-driven CADD methodologies for biosynthetic pathway optimization and molecule screening.
- Integrated synthetic biology with computational chemistry workflows for rapid in-silico experimentation.
- Automated ML pipelines using Python, PyTorch, and Scikit-learn on Linux, improving model testing and reproducibility.
Machine Learning & Bioinformatics Engineer
Myria Biosciences
- Processed and analyzed 1,000+ genomic and proteomic samples, reducing pipeline runtime by 35% using workflow managers and HPC clusters.
- Benchmarked variant calling pipelines, improving SNP detection sensitivity by 8% vs reference datasets.
- Built ETL workflows (Python, Pandas, SQL) to manage 50 GB/week multi-omics data with <2% error rate, enabling efficient data onboarding.
- Engineered a Neo4j knowledge graph with 10,000+ biological entities, improving R&D query speed by 50%.
- Delivered 30+ interactive dashboards and reproducible reports, accelerating research decisions across 3 clinical programs.
- Developed and containerized reproducible NGS and ML pipelines using Docker, Git, CI/CD, increasing workflow reliability and automation.
Data Scientist in Drug Bioinformatics
Helmholtz Institute (HIPS)
- Analyzed and integrated NGS and LC-MS/MS proteomics datasets, contributing to the discovery of 15 novel biosynthetic gene clusters.
- Developed ML models increasing expression efficiency prediction accuracy by 22%.
- Applied graph-based data science for pathway discovery; 3 computational predictions validated experimentally.
- Built Snakemake pipelines with version control, saving 40+ hours/month of manual processing time.
- Delivered reproducible bioinformatics pipelines now used by multiple research groups for genomic and biochemical analysis.
Research Assistant
KIST Europe
- Supported sequencing-driven synthetic biology projects, validating 100+ molecular cloning experiments.
- Led student training and workflow standardization, reducing onboarding time by 30%.
- Executed and analyzed ELISA, cloning workflows, and phage–host interaction studies to support bacteriophage engineering.
- Performed sequencing-based validation for construct integrity and experimental reliability.
Industries Experience
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Experienced in Biotechnology (3 years) and Pharmaceutical (0.5 years).
Business Areas Experience
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Experienced in Research and Development (3 years), Quality Assurance (2 years), Business Intelligence (1.5 years), and Information Technology (1.5 years).
Summary
Bioinformatician and DevOps-oriented Machine Learning Engineer with experience delivering scalable solutions across genomics, transcriptomics, and proteomics.
Skilled in reproducible NGS/ML pipeline development, workflow automation, and CI/CD-driven deployment across Linux and HPC environments.
Strong background in Python, R, and C++, with expertise in multi-omics data integration, ETL workflows, knowledge graphs (Neo4j), and developing dashboards and data products for research and clinical decision support.
Skills
- Ngs & Bioinformatics: Wgs, Wes, Rna-seq (Bulk & Single-cell), Methylome, Variant Calling, Annotation, Bioconductor
- Ml & Data Science: Scikit-learn, Pytorch, Pca/umap/t-sne, Clustering, Random Forest, Svm, Xgboost, Shap, Gnnexplainer, Graph Ml
- Devops & Infrastructure: Docker, Git, Bash, Linux Server Management, Ci/cd, Workflow Automation, Cloud Deployment
- Pipelines & Tools: Snakemake, Nextflow (Fundamentals), Biopython, Pandas, Numpy, Jupyter, Flask
- Data Engineering & Databases: Sql, Etl/elt, Api Pipelines, Neo4j Knowledge Graphs, Data Modeling
- Visualization: Plotly, R Shiny, Jupyter Dashboards, Rmarkdown, Interactive Reporting
Languages
Education
Saarland University
M.Sc. Bioinformatics · Bioinformatics · Saarbrücken, Germany
UET Lahore
B.Sc. Biomedical Engineering · Biomedical Engineering · Lahore, Pakistan · GPA: 3.721/4.0
Certifications & licenses
ETL And ELT In Python
(Short course)
Neo4j Certified Professional
GraphAcademy
Neo4j Graph Data Science Certification
GraphAcademy
Profile
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