๐Ÿ“–๐ŸŽ“ Now offering tutoring and consulting services ๐Ÿ“๐Ÿ“š

Experience#

Summary#

  • Microbiome scientist with 5+ years of experience developing and applying high-throughput molecular, computational, and statistical research methods to analyze 1000โ€™s of zebrafish gut microbiome samples

  • Robust data analytic skills in multivariate statistics and machine learning propel research experiments forward and gain data-driven insights

  • Demonstrated abilities to collaborate and take leadership in cross-laboratory experiments and extra-curricular projects

  • Experienced in written, oral and visual communication across scientific and public audiences

Education#

Oregon State University

Ph.D. Microbiology, minor in Biological Data Sciences

Expected 2025

Oregon State University

B.Sc. Bioresource Research, options in Bioinformatics and Genomics

2020

Research#

Investigate how environmental factors (diet, pollutants, pathogens, etc.) interact with the gut microbiome to influence host health using the zebrafish model organism.

Projects:

  • Measure resilience of gut microbiome to chronic exposure of antibiotics (Sieler, in-development)

  • Assess gut microbiome resiliency to anthropological impacts such as temperature and pathogenic exposure (Sieler, in-development)

  • Investigate the joint interaction effects of diet and pathogen exposure on gut microbiome succession (Sieler, in-prep)

  • Measure the effect of nanoplastics on the mouse gut microbial community (Szule 2022)

  • Potential and challenges of deep transfer learning in microbiome science (David 2021)

  • Meta-analysis of zebrafish gut microbiomes phylogeny (Sharpton 2021)

  • Microbial Bioinformatics Hub: information, methods and tools related to analyzing microbiological data

  • The impact of the environmental pollutant Benzo(a)Pyrene on gut microbiomes of juvenile zebrafish (Stagaman, in-development)

Tools:

  • Programming: R, Python, Git, DADA2, Phyloseq, HTML, CSS, Unix/Linux, C++

  • Bioinformatics: 16S sequencing (DADA2 & Phyloseq), Metagenomics (FastTree & HMMER)

  • Documentation: Sphinx & ReadTheDocs

Skills:

  • Analytic: data management and analysis, multivariate statistics, machine learning

  • Presentation: oral and written communication, pipeline documentation

  • Project Management: leadership, experimental design, coordination and analysis, cross-laboratory collaboration

  • Other: see more Skills below

Work#

National Microbiome Data Collaborative - Ambassador

Mar 2024 - Present

The NMDC ambassador program recognizes and fosters early career scientistsโ€™ efforts to incorporate inclusion, diversity, equity and accountability (IDEA) principles to promote findable, accessible, interoperable, and reusable (FAIR) microbiome research data and workflows.

Pacific Northwest National Laboratory - PhD Bioinformatics Intern

June 2023-Present

Projects:

  • Batch Correcting Lipidomics data

    • Analyzed dilution series experiment to resolve batch effects in lipidomics datasets

Tools used:

  • R

MJSieler Consulting - Owner

May 2022-Present

Projects:

  • Virtual Fish (GitHub)

    • Designed, developed, and deployed educational video game software for clients

    • Educational software used to fulfill grant requirements for communicating scientific research

Tools used:

  • C#, Unity, Git

Awards, Honors & Fellowships#

Oregon Museum of Science and Industry

Science Communication Fellow

  • Received certified training in informal science education and engagement with public audiences to increase their understanding of STEM research

2020-Present

ARCS Foundation

ARCS Scholar

  • Recognized for my early significant contributions to scientific research, I was awarded the prestigious ARCS Scholar grant ($18,000)

2020-2023

Certificates#

Machine Learning Specialization

In-progress

  • Introduction to modern machine learning, including supervised and unsupervised learning

  • Supervised and unsupervised machine learning, advanced learning algorithms

  • Use Python to build and train machine and deep learning models

Data Science and Machine Learning Bootcamp with R

2021

  • Program with R to wrangle, clean, analyze, and visualize data.

  • Apply advanced statistics and machine learning to gain useful insights.

Skills#

Programming:

Statistics and Data Analytics:

Bioinformatics:

  • R

  • Python

  • C# (Unity)

  • Git

  • HMTL & CSS

  • C++

  • UNIX/Linux

  • Advanced linear regression

  • Machine learning

  • Model building and testing

  • Big data query

  • Data mining

  • 16S sequencing

  • Metagenomics

  • DADA2

  • Phyloseq

  • Mothur

  • HMMER

  • Metabolomics

  • FastTree

Laboratory:

Other:

Languages:

  • Zebrafish husbandry

  • Bacterial culturing

  • DNA extraction

  • PCR amplification

  • Gel electrophoresis

  • Microsoft Office Suite

  • Adobe Photoshop and Illustrator

  • Blender

  • English (native)

  • German (C1, advanced)

  • Spanish (beginner)

Download Resume & CV#

Resume (one page)

CV


Return to top.