Research Computing's Services
Overview
Research Computing at Dartmouth offers a wide range of computing services to the Dartmouth community to facilitate the advancement of research.
We operate the supercomputer cluster at Dartmouth, allowing you to run compute-intensive, large-memory programs quickly. We provide data storage, accessible both on and off campus and from multiple devices, on DartFS, a next-generation storage solution, as well as databases and Virtual Machine environments.
RC also provides support for and access to research software applications such as Qualtrics, Jupyter, and ArcGIS Online as well as custom software development, and we can assist academics in creating data graphics or animations to illustrate their scholarship/research.
Our staff can provide consulting and expertise to optimize your code, as well as in specific fields of study, including GIS, Life Sciences, Humanities, and more. We also hold workshops and other training to help you most effectively use software such as RStudio, and our field specialists hold office hours every week.
Most of our services are available at no cost to members of the Dartmouth research community, including faculty, post-docs, graduate, and undergraduate students.
Please do not hesitate to contact us at Research.Computing@dartmouth.edu. We will be happy to meet one-on-one, in groups/labs, or just come by and we will answer any questions for you.
Research Computing offers a wide range of services from research software support to code development and grant support. Most of our services are available at no cost to members of the Dartmouth research community including faculty, post-docs, graduate, and undergraduate students.
Software Support
We provide technical support and installation services for research software applications. Note: we offer support for research software, for help with non-research applications such as Microsoft Office please contact Dartmouth Computing.
Data Support
We provide data management services including data storage, sharing, and access via web interfaces and support for off-site collaborators.
Code Development
We develop, debug, and optimize code to effectively use resources and improve code performance, and help you collaborate with users to convert sequential programs to run in parallel.
Review Offerings from Research Software Engineering
Grant Support
We facilitate grant proposal writing by providing configuration and pricing for a grant’s proposed hardware and software.
Research Engagement and Data Services
Research Engagement and Data Services Team
Field Specific Support
Our team provides expert consultation and hands-on support across a broad spectrum of data science, analytics, and computational disciplines to advance research across all domains at Dartmouth. Our services include:
- Statistics: We support researchers at all stages of their projects, from experimental design and power analysis to data cleaning, statistical modeling (including multilevel and longitudinal models), validation, and interpretation. We are well-versed in both frequentist and Bayesian methods, with expertise in reproducible workflows and transparent reporting.
- Bioinformatics & Life Sciences: We assist with high-throughput sequence data, variant and junction calling, annotation, visualization, and integrative -omics analyses. We also support pathway/network analysis, functional enrichment, and applications of machine learning in biomedical research.
- Data Visualization: We help researchers transform complex datasets into compelling, interpretable visuals using tools like R, Python, and Tableau. We specialize in static and interactive dashboards, longitudinal and geospatial visualizations, and publication-ready figures.
- Text Analysis & Natural Language Processing (NLP): We support automated document classification, sentiment analysis, topic modeling, and named entity recognition. We also help develop, fine-tune, and evaluate language models for biomedical, humanities, and social science applications.
- Artificial Intelligence & Machine Learning: We provide guidance on supervised and unsupervised learning, deep learning, and the ethical use of AI in research. Our team assists in model selection, training, tuning, evaluation, and deployment, with experience in domain adaptation and synthetic data generation for sensitive contexts.
- Geographic Information Systems (GIS): We support GIS software setup, spatial data integration, and spatial analysis. We also help design maps and spatial models tailored to public health, environmental, and sociological research.
- Research Design & Responsible Data Practices: Our consultants can help shape studies with robust research design, pre-registration plans, ethical use of data, and alignment with FAIR data principles and reproducibility standards.
Informatics & Applications
The Research Engagement and Data Science team at Dartmouth Research Computing partners with researchers across disciplines to advance data-driven discovery. We specialize in applying cutting-edge informatics and data science methods to tackle complex research questions in the biomedical sciences, social sciences, digital humanities, and beyond.
Whether you’re launching a new project, troubleshooting existing analyses, or exploring innovative technologies, our team is here to help. We offer:
- Consultations for Long-Term Collaborations: We embed with research teams for extended support—from grant development and study design to data analysis, visualization, and manuscript preparation. Our collaborative approach ensures continuity and in-depth understanding of your research goals.
- Short-Term Lab Visits and Just-in-Time Help: Need quick guidance on coding, software tools, or analytic approaches? We’re available for one-time consultations, drop-in support, and short lab sessions tailored to your immediate needs.
- Workshop Development and Instruction: We create custom workshops and tutorials for lab groups, departments, and graduate programs. Popular topics include machine learning in R or Python, natural language processing, reproducible research, version control with Git, and best practices for FAIR data.
- Expertise in Advanced Data Science Techniques: Our team has hands-on experience in high-dimensional modeling, unsupervised learning, predictive analytics, network analysis, biomedical text mining, data wrangling, and the use of large language models (LLMs) for research tasks.
We’re committed to helping Dartmouth researchers maximize the value of their data, from experimental planning to actionable insights. Whether you’re working with structured health data, unstructured clinical notes, survey data, sensor streams, or digital texts, we’re here to help you translate data into discovery.
Visualization
We Assist academics in creating data graphics or animations to illustrate their scholarship/research.