Thursday, July 16, 2026
Fall 2026 course offering, NFSC-415/615: R for Applied Genomics
NFSC-415/615: R for Applied Genomics, Fall 2026
Instructor: Ryan Blaustein, Ph.D. (rblauste@umd.edu)
Location: Woods Hall, Room 1127
Time: Tuesdays and Thursdays, 9:30-10:45am
Office Hours: Contact instructor for appointment
Course Objective: Genomics research is increasingly important in agriculture and biotechnology. New advances in understanding genome function and, at the foundation of food systems and nutrition, interactions in complex microbiomes (microbial communities and their genes) have come from the generation and processing of ‘big data.’ Essential to applied genomics research is knowledge of programming language for statistical analysis and interpretation of large datasets. NFSC-415/615 will train students with skills for programming in R, the primary open-source language used in the agricultural and life sciences, and how to analyze genomics and microbiome data.
Course Description: This course will provide a comprehensive introduction to R, along with statistical concepts and algorithms used in whole genome sequencing (WGS) and microbiome analysis. Most of the course will deal with R scripts and packages, though additional software tools may be incorporated. This course will consist of three modules:
1. Basics of the R language
2. Genomic applications in food science and nutrition
3. Introduction to omics data analysis
Prerequisites: Students are expected to have taken at least one semester of biostatistics, such as BIOM-301 or BIOM-601, and to have background understanding of principles in molecular biology, or permission granted from the instructor.
Student Learning Outcomes: After completion of this course, students will be able to: 1. Write R scripts and use coding language
2. Navigate open-source software applications and genomics repositories, such as in the National Center for Biotechnology Information (NCBI) archives
3. Perform basic genome and microbiome analysis
Grading: Students will complete weekly exercises and module projects to demonstrate knowledge and application of concepts discussed in class.
Course Assignment Final Grade Scale*
Weekly exercise, 10 points, x10 = 100 points A+ (97-100%); A (93-96%); A- (90-92%); Module 1 Project, 100 points B+ (87-89%); B (83-86%); B- (80-82%); Module 2 Project, 100 points C+ (77-79%); C (73-76%); C- (70-72%); Module 3 Project, 100 points D+ (67-69%); D (63-66%); D- (60-62%); Term paper, 100 points (NFSC-615 only) F (<60%)
*The final grade reflects the student’s understanding of the subject material. At the end of the semester, the final grade scale may be adjusted.
Communication: All lecture materials, including R-scripts, papers for discussion, and assignments will be posted to CANVAS on a weekly basis.
Resources and Software: Students need to install the free software R (https://www.r project.org/) and R-studio (https://posit.co/download/rstudio-desktop/) on their personal computer and bring the computer to each lecture.
Assignments:
Weekly Exercises – Given the fast-paced nature of this course, weekly exercises will be assigned to support continuous learning and skill development. These ‘take-home quizzes’ will be designed to build proficiency in R scripting and reinforce key course concepts. Exercises will be due on the Tuesday following the week in which they are assigned (e.g., a Week 1 assignment is due Tuesday of Week 2).
Module Projects – At the conclusion of each module, students will complete a comprehensive project to demonstrate their ability to apply R programming and integrate course concepts. Projects will include annotated R scripts and accompanying summaries that reflect core coding skills, e.g., use logical and mathematical operators, sub-setting data, working with apply family functions, writing loops and original functions, navigating conditional statements, generating data visualizations, and/or applying statistics to answer relevant analytical questions. Example datasets (e.g., microbiome and RNA-seq) will be provided for these projects.
Term Paper (NFSC-615) – Graduate students will develop a research proposal focused on genomics applications covered in the course. Proposals may address either applied or fundamental research questions and must incorporate at least two of the following approaches in the detailed experimental design and plans for the computational analysis: • Whole genome sequencing
• Amplicon sequencing (e.g., 16S rRNA gene)
• Shotgun metagenomic sequencing
• Transcriptomic sequencing
• Other area approved by the instructor
The paper is limited to 10 pages (excluding references) and is due Friday, December 4, 2026.
Late assignments will receive a 20% reduction in the assignment grade for each week that it is late. Assignments that are not submitted after 2 weeks will receive a 0.
Policy on Artificial Intelligence (AI) tools: Understanding how and when to use generative AI tools (such as ChatGPT and Gemini) is quickly emerging as an important skill for future professionals. While students are permitted to use AI for general brainstorming, every element of the above class assignments must be prepared by the student. The use of generative AI tools to replace independent research or in an unreferenced way will be treated as plagiarism.
Honor Code: It is expected that all students adhere to the Honor Code administered by the UMD Student Honor Council. Any student involved in academic dishonesty will be reported and will receive a course grade consistent with university policies. For more information see: http://www.shc.umd.edu/code.html.
Accommodations: If you wish to discuss academic accommodations, please provide documentation from the Accessibility and Disability Support Service (301-314-7682; adsfrontdesk@umd.edu). If you are encountering personal difficulties during the course, please let the instructor know as soon as possible. The UMD Counseling Center (301-314-7651) is available for assistance as well.
Schedule of Classes:
Week | Date | Topic | Description |
MODULE 1: Basics of the R language | |||
1 | 09/01/26 | Introduction to R | R language, R studio, Bioconductor, software installation |
09/03/26 | language elements, i.e., vectors, matrices, lists, data frames, factors | ||
2 | 09/08/26 | Labor Day - no class | |
09/10/26 | Basic operations | read and write, import, export, assign values to variables, browse data | |
3 | 09/15/26 | Coding functions I | summary stats (mean, stdev, min/max), compare elements |
09/17/26 | string manipulation, subset, ordering | ||
4 | 09/22/26 | Coding functions II | using apply family functions, loops |
09/24/26 | writing custom functions | ||
5 | 09/29/26 | Graphing features | ggplot2, graphical parameters |
10/01/26 | preparing high-quality figures | ||
MODULE 2: Genomic applications in food science and nutrition | |||
6 | 10/06/26 | Next-generation sequencing | overview of sequencing technologies |
10/08/26 | generating data, accessing repositories (NCBI), large-scale project examples | ||
7 | 10/13/26 | Fall break - no class | |
10/15/26 | Applications for genomics in food science and nutrition | Overview of whole genome sequencing, microbiome, metagenomics | |
8 | 10/20/26 | Experimental design for omics projects | sampling applications and limitations |
10/22/26 | hypothesis testing, data distributions | ||
9 | 10/26/26 | Univariate and multivariate statistics | t-test, ANOVA, Wilcoxon, Kruskal Wallis, linear models, correlation |
10/29/26 | bootstrap, permutational ANOVA, PCA, PCoA, NMDS | ||
10 | 11/03/26 | Machine learning applications | overview of models |
11/05/26 | caret package, random forest example | ||
MODULE 3: Introduction to omics data analysis | |||
11 | 11/10/26 | Working with WGS data | quality control, genome assembly, annotation |
11/12/26 | exploring features with BLAST; e.g., antimicrobial resistance, virulence | ||
12 | 11/17/26 | Microbiome analysis | R and command line tools for amplicon datasets |
11/19/26 | characterizing microbial diversity, data visualization | ||
13 | 11/24/26 | shotgun metagenomics applications for functional profiling | |
11/26/26 | Thanksgiving break - no class | ||
14 | 12/01/26 | Functional genomics | overview of gene expression analysis such as with Blast2GO |
12/03/26 | pathway assignment, e.g., KEGG, COG | ||
15 | 12/08/26 | Multi-omic applications | new directions and advancements in workflows |
12/10/26 | |||
NRAC Director Search
Associate Professor/Professor OR Senior/Principal Agent OR Senior/Principal PTK Ranks AND Director, Northeast Regional Aquaculture Center x
Job Description Summary
The Northeast Regional Aquaculture Center (NRAC) seeks a visionary leader to serve as the Center’s next Director. NRAC’s mission empowers Northeastern aquaculture through cutting-edge science and collaborative partnerships, driving sustainable growth and innovation for a thriving industry and a healthier environment. Building on the Center’s thirty plus-year legacy of providing leadership in addressing the complex issues facing the Northeastern aquaculture industry through research, outreach, and collaborative partnerships, the new Director has a unique opportunity to expand the Center’s growth, visibility, and impact.
Headquartered at the University of Maryland, NRAC is one of five Regional Aquaculture Centers established by the U.S. Congress. Funded by the U.S. Department of Agriculture and representing 12 states and the District of Columbia, NRAC develops and sponsors cooperative regional research and Extension projects in support of the aquaculture industry in the northeastern United States.
The Center’s research and extension priorities are established by the Technical Advisory Committee (TAC) and the Industry Advisory Committee (IAC). TAC includes key aquaculture researchers and Extension agents in the region, while the IAC represents principal commercial aquaculture interests in the Northeast.
The Center’s work utilizes a three-pronged approach to address its mission. First, the Center funds research and Extension projects that meet the aquaculture industry's priorities established by TAC and IAC. Second, the Center’s work focuses on outreach, including all aspects of the Center’s communications, to distribute research findings through videos, social media, newsletters, webinars, and other venues. Collaboration and working with the NRAC Board and the northeast aquaculture and seafood communities is the third cornerstone of the Center’s work. The Board, representing the region's aquaculture industries, academic institutions, and government agencies, provides overall direction and management of NRAC.
For more information about this position including pay, how to apply, and requirements please click here
Job opportunity: forest ecology technician at SERC
BIOLOGICAL TECHNICIAN IS - 0404 7-1
MAJOR DUTIES
The incumbent will support tree monitoring and field maintenance activities at BiodiversiTREE, a large experimental forest at the Smithsonian Environmental Research Center.
Monitoring duties include assisting with and sometimes leading the following activities: tracking tree survival and growth; collecting roots and analyzing morphological root traits as well as collecting samples for identifying mycorrhizal communities; using ingrowth cores to measure fine root production, soil carbon storage, and nitrogen retention; collecting soil water and tree sap for isotopic analyses; using ground-penetrating radar to measure coarse root biomass; and using LiDAR to estimate forest canopy attributes. Accurate data collection requires proficiency with ArcGIS Field Maps, GPS navigation, and strong spatial reasoning to locate designated planting sites and navigate plot treatments.
Field maintenance responsibilities include mowing, applying herbicide in accordance with established safety guidelines, and manually removing unwanted or encroaching vegetation. The incumbent will also identify woody and herbaceous plant species, ensure proper tagging and documentation, and support data management — including developing data collection formats and contributing to a quality assurance program.
KNOWLEDGE REQUIRED BY THE POSITION
Knowledge and Skills
The incumbent should have a working knowledge of forest ecology and experience identifying woody and herbaceous plant species common to the US mid-Atlantic. Familiarity with standard ecological field methods is required, including techniques for measuring tree survival and growth, root collection and trait analysis, and soil sampling. Proficiency with Office software and R statistical software is expected. Experience with ArcGIS Field Maps, GPS tools, LiDAR, ground-penetrating radar, isotopic analyses, or mycorrhizal community assessment is beneficial but not required. The incumbent should be comfortable supporting data management tasks, including, writing protocols, developing data collection formats and contributing to quality assurance. A supervisor is available for guidance on unusual or unexpected problems.
Physical Requirements
Most work is performed outdoors in the field, with occasional sedentary laboratory or office tasks. The role requires prolonged standing, walking over uneven terrain, lifting and carrying loads up to 50 lbs, and operating hand tools and motorized vehicles. The incumbent must be prepared for extended exposure to heat, cold, wet conditions, stinging and biting insects, poisonous plants, and similar environmental hazards, and should take appropriate safety precautions. Travel between field sites may be required.
WORK ENVIRONMENT
The work environment includes both typical office and laboratory settings, but the incumbent will primarily work outdoors in terrestrial field environments of the Chesapeake Bay region and similar areas. Most days will involve considerable time spent outside, often under conditions of extreme heat or cold, exposure to poisonous plants, stinging and biting insects, and various forms of inclement weather. Field sites are not within walking distance of restroom facilities; however, a restroom is available at a nearby field location and may be accessed as needed.
Salary: $57,736 plus health benefits
Appointment Type: Term appointment for 1 year, with the second and third years of funding contingent upon satisfactory progress. (This is not a Federal position)
Deadline: Open until filled. Review of applications will begin immediately. We anticipate a start date in early fall 2026.
Location: This position is based at the Smithsonian Environmental Research Center in Edgewater, Maryland. The SERC campus contains nearly 2,700 acres of forest, agricultural areas, wetlands, and streams, and sits directly on the Rhode River estuary on the western shore of the Chesapeake Bay. SERC is a research center of the Smithsonian Institution and is located close to the historic seaport of Annapolis, Maryland, the US capital in Washington D.C., and Baltimore, Maryland, with numerous nearby universities and opportunities for work and play.
The position is open to all candidates eligible to work in the US. The Smithsonian Institution is an Equal Opportunity Employer. We believe that a workforce comprising a variety of educational, cultural, and experiential backgrounds support and enhance our daily work life and contributes to innovative science and creative solutions. We strongly encourage candidates from all backgrounds to apply. We recognize that each applicant will bring unique skills, knowledge, experiences, and background to these positions. The Smithsonian Institution is an equal opportunity employer, committed to a policy of nondiscrimination on the basis of race/ethnicity, national origin, gender identity and expression, sexual orientation, age, religion, marital/parental/caregiver status, and disability.
The Smithsonian Institution provides reasonable accommodation to applicants with disabilities where appropriate. Applicants requiring reasonable accommodation should contact SERC_HR@si.edu. Determinations on requests for reasonable accommodation will be made on a case-by-case basis. To learn more, please review the Smithsonian’s Accommodation Procedures.
To apply, please send the following as a single PDF document to John Parker (parkerj@si.edu): cover letter summarizing relevant experience, Curriculum Vitae, and the names and full contact information (email, phone, postal address) of three references.
Travel scholarship for students
Check out this travel scholarship opportunity undergraduates and graduate students.
Friday, July 10, 2026
Smithsonian's National Zoo PAID Internships
Hello, the Smithsonian’s National Zoo has 9 paid internships this upcoming fall semester. Please share this information with any student that may be interested.
These internships will be highly competitive. If a student is interested, I encourage them to apply to multiple internships and to write an individualized statement of interest for each. Note that one internship is located in Virginia, not DC.
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