The Mellon College of Science (MCS) is home to four departments and many programs and research centers that cross disciplines. We approach scientific problems from fresh angles using creative interdisciplinary approaches while drawing on our departmental strengths in the core sciences.
Our Pittsburgh Supercomputing Center (PSC) within MCS is seeking an expert Scientific Project Manager to join PSC's Public Health Applications group. Our group empowers public health decision-making to mitigate a wide range of global public health threats including influenza, malaria, obesity, and antibiotic-resistant bacteria. Our dynamic team includes scientists, modelers, software developers, and high-performance computing (HPC) specialists. We works closely with PSC’s other science and technology groups, particularly Artificial Intelligence and Big Data, Advanced Systems, and User Support for Scientific Applications.
In this role, you will combine a solid technical understanding of software development and data analysis with effective project management principles to drive progress in multi-disciplinary scientific projects in public health modeling, translating modeling tools to new and broader audiences for national and international public health decision support. You will also facilitate and add to developing data-intensive analyses and visualizations, coupling sophisticated software tools with accessible, user-focused services and interfaces, and developing large-scale simulation software for state of the art computational hardware. You may also participate through a matrix-managed approach to PSC’s AI and Big Data group, focusing on developing AI approaches to real-world problems. Your work will also entail publishing, presenting, and leading or contributing to attracting future funding.
The Public Health Applications group currently has several openings for both software development and technical/scientific project management roles. If you have experience applicable to multiple roles, you should apply to the single position that provides the best fit with the understanding that the distinction between these roles can be flexible.
Your core responsibilities will include:
Coordinating and overseeing scientific projects, working with external partners and collaborators to define objectives and requirements and ensure that deliverables are successfully produced on schedule.
Working closely with collaborators at PSC and other institutions to facilitate advances in computational public health modeling.
Preparing documentation, examples, and training materials, and participating in workshops, briefings, and broad efforts in education, outreach, and training.
Develop research opportunities and attract external funding. Lead or assist with the development of proposals to national agencies, foundations, and other entities.
Documenting results, communicating significant findings through publications, conferences, or other professional channels.
Build statistical models and frameworks to help answer public health research questions.
Work closely with software developers to craft computational public health models.
Design, execute, and evaluate large in silico simulation experiments using a variety of computational models.
Prepare and contribute to manuscripts for publication in peer-reviewed scientific journals.
Produce charts, graphics and presentations to clearly communicate analysis results.
Some travel may be required, as well as the flexibility to work effectively with external collaborators in different time zones.
You will demonstrate:
Project management experience using leading frameworks (e.g. Jira, Zoho, MS Project, RedMine)
Experience managing large NSF- and/or NIH-funded projects
Peer-recognized expertise in developing data-intensive modeling applications; substantial personal contributions to publications, awards, and grants for research in these fields
Demonstrated ability to plan and execute individual and collaborative research
Experience acting as a team leader or technical project manager
Peer-reviewed publications in public health, disease transmission modeling, or decision analysis
Demonstrated proficiency in the development or use of large-scale simulation models
Understanding of the principles of Equation-based (EBM) and/or agent-based (ABM) modeling
Authorship of and significant contributions to peer-reviewed publications
Bachelor's degree in statistics, computer science or other quantitative or computational discipline, or equivalent combination of training and experience required. Advanced degree (MS, MBA, PhD) in statistics, computer science, or a computational science or engineering discipline or MBA with project management focus preferred
Experience planning, organizing, and controlling the performance of work in the context of complex, technical projects
Excellent communication, technical writing, and public presentation skills
Ability to work as a part of a team on multiple concurrent projects and independently when required
Excellent analytical, technical, and analytical skills
Development of quantitative analysis, reports, and models to support decision-making
Experience using common statistical packages in Microsoft Excel, R, Python, and possibly others. Comfortable working in a Linux environment.
Ability to apply mastery and deep understanding in a specific field (e.g. machine learning or statistics) to practical scientific or technical projects in other fields
Practical proficiency with one or more general-purpose interpreted language (Python, R)