Education

Education Overview

Continuing the exponential increase in scientific and medical breakthroughs directly depends on our commitment to teaching the next generation of independent researchers. Our department is dedicated to providing cutting-edge research experiences and first-rate didactic training to students at the high school, undergraduate, and graduate levels, through both internal, intra- and inter-institutional programs to train our students in the rapidly evolving and highly interdisciplinary field of computational biology. Our department has implemented a Tiered Mentoring and Training (TMT) framework, which provides students with numerous opportunities to learn from multiple faculty, postdoctoral fellows, graduate students, and other summer undergraduates from a variety of areas and perspectives. These interactions also provide important professional development opportunities for these early-stage and nascent investigators, who will be future teachers and mentors

The Joint Carnegie Mellon University-University of Pittsburgh PhD Program in Computational Biology (CPCB) provides interdisciplinary training in computational biology supported by leading experts from two renowned computer science and biomedical research institutions. With a focus on areas like cellular and systems modeling, computational structural biology, bioimage informatics and computational genomics, the CPCB program positions its students to tackle scientific questions at the interface of life, physical, engineering and computer sciences.

Online applications typically open in early September and close in mid-December. For specific application dates and program information, visit https://www.compbio.cmu.edu/prospective-students/index.html.

The Computational Biomedicine and Biotechnology Master of Science program empowers students to take on key roles in health care, biotech, academia and beyond. The MS program focuses on translating cutting-edge computational technologies into real-world advances in biomedicine and biotechnology. The curriculum is designed to equip students with the skills they need to meet current challenges in biotechnology using computational, mathematical and statistical techniques.

Computational Biomedicine and Biotechnology enrolls students each fall, but spring entry may be possible. We encourage prospective students to submit applications as early as possible, as the admissions committee will begin reviewing files as they are received, until we reach capacity. Applications received later will be considered for admission the following term. The application will open in early September. Learn more

The Training and Experimentation in Computational Biology (TECBio): “Simulation and Visualization of Biological Systems at Multiple Scales” Research Experiences for Undergraduates (REU) program is a 10-week summer program that will provide a challenging and fulfilling graduate-level research experience to undergraduate students. Students will work on a cutting-edge research project in the emerging fields of computational and systems biology, such as computational structural biology, cell and systems modeling, computational genomics, computational drug discovery and bioimage informatics.

TECBio students will engage in the following activities:

• Participate in a weekly journal club,
• Attend research and career seminars organized specifically for the program,
• Take part in an ethics forum that will instruct them in the responsible conduct of research,
• Present their work at a Pittsburgh-wide annual research symposium, and
• Experience various social and cultural activities available in Pittsburgh.

Applications typically open late November/early December and close mid-February. For more info, visit https://www.tecbioreu.pitt.edu/ or email us at tecbio@pitt.edu.

The CompBio Academy (formerly Drug Discovery, Systems and Computational Biology (DiSCoBio) Academy) introduces rising high school juniors and seniors to the emerging fields of research that use both computational and experimental approaches to answer fundamental questions in cancer biology and related disciplines, including:

• Computational Structural Biology (studying how proteins move and interact with each other)
• Drug Discovery (theoretical and experimental designing and testing of candidate drug compounds)
• Genomics/Bioinformatics (analyzing large data sets of sequencing and other data)
• Image Analysis/Informatics (training a computer how to see and analyze biological image data)
• Systems Biology (tackling biological questions using an integrated, holistic approach)

In addition to a primary research experience in one of these fields, scholars will learn fundamental concepts and gain hands-on training in the tools and techniques central to each field. Professional development activities will complement the research and didactic training to help prepare scholars for careers in science and/or medicine. Scholars should expect an immersive, challenging and fulfilling research and training experience in a fast-growing area of cutting-edge biomedical research. For more information visit https://www.discobio.pitt.edu/.

Applications open December 2023 and close Feb. 11, 2024. For more info, visit https://www.discobio.pitt.edu/how-to-apply/.

Tentative Program Dates: June 17–Aug. 2, 2024

The “Adopt a Proto-Gene” Initiative is a research education program in computational biology for undergraduate students and educators. Students will gain hands-on experience in proto-gene research, an emerging field that focuses on understanding genetic elements.

Participants in the program will engage in:

• Teaching modules for undergraduate students to explore proto-genes in the model eukaryote Saccharomyces cerevisiae
• Virtual workshops to assist faculty with undergraduate teaching modules at their home institutions
• Paid immersive summer research experiences for undergraduates in The Carvunis Lab at the University of Pittsburgh

Applications for the summer research program are typically due in March. For more information, please email castilho@pitt.edu. 

Workshops

Hands-on Workshop on Computational Biophysics

This workshop was presented by members of the National Center for Multiscale Modeling of Biological Systems (MMBioS) from the University of Pittsburgh and the members of the Theoretical and Computational Biophysics Group (www.ks.uiuc.edu) from the University of Illinois at Urbana-Champaign. It covered a wide range of physical models and computational approaches for the simulation of biological systems including ProDy,NAMD and VMD. The course was based on case studies including the properties of membranes and membrane proteins, mechanisms of molecular motors, trafficking in the living cell through water and ion channels, signaling pathways and druggability simulations. Relevant physical concepts, mathematical techniques, and computational methods were introduced, including force fields and algorithms used in molecular modeling, molecular dynamics simulations on parallel computers, elastic network models, and steered molecular dynamics simulations.

MMBioS Workshops

The annual MMBioS workshops provide hands-on and state-of-the-art training in topics related to our Technology Research & Development projects and other expertise present within MMBioS participants. These workshops are aimed at both experimental and computational scientists, and promote collaboration between the groups.

MCell Workshop

This workshop was organized by the Center for Multiscale Modeling of Biological Systems and covered theory and practice for the design and simulation of models focused on diffusion-reaction systems such as neurotransmission, signaling cascades, and other forms of biochemical networks. The lastest version of the MCell simulation environment (www.mcell.org) were introduced, including new Monte Carlo methods for 3-D simulation of reactions in solution and on arbitrarily shaped biological surfaces. During the workshop, we also introduced:

1. Novel tools to incorporate rule-based modeling techniques into MCell simulations based on the BioNetGen Software.
2. Our new MCell model creation and visualization framework, CellBlender, that builds on our previously developed model creation pipeline.