Integrating Research and Careers on the Phenotype
A National Science Foundation Research Traineeship (NRT)
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Predicting an organism’s phenotype remains one of the central challenges of modern life science. Understanding how different scales of biological organization from the genome to the environment determine phenotypes and their consequences is a critical step in solving societal problems of human health, food security, and response to global climate change. The next generation of scientists, whether they work in academic careers or other settings, must be able to integrate and communicate their research across these scales and bring modern computational and quantitative approaches to bear on big data.
EXPAND seeks to address these central challenges by recruiting, training, and mentoring a diverse community of life sciences students with a broad intellectual platform to break down historic disciplinary silos. Broad scientific training is complemented with stage-specific professional development and exposure to a wide range of non-academic career opportunities.
Pillars to EXPAND...
The conceptual breadth of science
Career options for graduates
The diversity of scientists in the life sciences
Opportunities to Join EXPAND
EXPAND Courses, Fall 2022
Interested in developing your professional skills? Want to expand your quantitative expertise? Check out the EXPAND Program's Fall offerings listed below, and click here to learn more about each.
Professional Skills Courses
GSCI 8500-001: Integrative Studies of the Phenotype (1st & 2nd year)
GSCI 8500-003: Career Design for Life Sciences (3rd or 4th year)
GSCI 8500-002: Professional Transitions Seminar (4th or 5th year)
BIOL 8240: Professional Skills for the Life Sciences (1st year)
Quantitative Courses
EVSC 5040: Advanced Ecological Data Analysis
PSYC 7710: Quantitative Methods I: Probability & Statistical Inference
BIMS 8380: Basic Study Design and Practical Statistics
BIMS 8382: Introduction to Biomedical Data Science
EVSC 7080: Quantitative Methods in Environmental Sciences
PHS 7000: Introduction to Biostatistics I
PHS 7170: Data Management in Population Health with SAS
PSYC 7559: Computational Neuroscience
PSYC 8730: Dynamic Systems Analysis
Open House - Tuesday, September 13, 2022, 3:30 - 5 pm in Gilmer 490
Interested in learning more about our program and course offerings? Then drop by our Open House on Tuesday, September 13th, from 3:30 - 5 pm in Gilmer 490! Our 2021-2022 fellows will present what they learned during their summer internships and will be available for a Q&A afterwards. We will also have poster presentations from laboratories conducting interdisciplinary research. We will be serving light refreshments and would love to answer any of your questions!
If you wish to present a poster highlighting your integrative research, please submit your abstract (250-word max) to expand@virginia.edu by 11:59 pm on September 1st. There will be a $250 prize for the best poster!
EXPAND is Recruiting at SACNAS and ABRCMS Conferences
The EXPAND Program will have recruiting tables at SACNAS and ABRCMS Conferences! SACNAS' National Diversity in STEM Conference (NDiSTEM) will take place October 27-29th, 2022 in San Juan, Puerto Rico. The ABRCMS Conference will take place November 9-12, 2022 in Anaheim, California. Please stop by to say hello!
Reintegrating the Phenotype
This research cluster realigns doctoral training to respond to complex societal questions regarding the phenotype by bringing together faculty and students in cell and developmental biology, neuroscience, evolution, ecology, psychology and environmental sciences. Participants will have the opportunity to explore a variety of topics, such as forecasting how changing environments will impact the biodiversity of phenotypes and species and understanding how the production and variation of disease and resistance phenotypes affect the development of effective management and treatment strategies. Alongside their disciplinary focus, doctoral fellows will be mentored as creative thinkers and productive collaborators across lab groups.
