Song Lab is recruiting!
The Song Lab in the Department of Biological Sciences at the University of Pittsburgh is now recruiting a postdoctoral researcher, a research technician, and a PhD student
Lab Overview
The Song Lab is a new research group in the Department of Biological Sciences at the University of Pittsburgh, focused on understanding how global change alters phenology and biodiversity, and how these ecological changes interact with human activities.
Our research operates at the intersection of environmental data science and global change biology. We integrate large-scale observational and experimental datasets and cutting-edge analytical tools—from hierarchical Bayesian modeling to artificial intelligence. We aim to provide both theoretical insights and practical solutions to the challenges posed by our rapidly changing world.
Position 1: Postdoctoral Researcher
We are seeking a postdoctoral researcher to lead a project on the seasonal dynamics of biodiversity under environmental change. This position will contribute to understanding how phenological shifts at the population level scale up to affect seasonal dynamics of community composition and species interactions. There is flexibility for the researcher to shape the direction of the work based on their interests and expertise at the intersection of phenology and biodiversity. The project will leverage long-term high-resolution community composition datasets (e.g., airborne pollen, phytoplankton, or other study systems). Analyses may include ordination, multivariate time series modeling, and network analysis. This is an opportunity to contribute to theoretical frameworks and to publish high-impact papers through synthesis of big data. There will also be opportunities to collaborate with internal and external partners, co-mentor students, and contribute to grant development.
Preferred domain knowledge:
- Strong background in ecology or a related field, with interest or experience in phenology, community dynamics, and/or species interactions
- Experience investigating ecological patterns over time
- In-depth knowledge of at least one study system (e.g., grassland, bird, insect, microbial) and broad familiarity with several others would be beneficial
Preferred technical skills:
- Proficiency in multivariate statistics and time series analysis
- Proficiency in R (and preferably Python) for ecological data analysis
- Ability to manage and synthesize large ecological datasets (e.g., observatory networks, remote sensing, or environmental sensor data)
- Familiarity with network analysis, Bayesian modeling, or machine learning would be beneficial
This is a full‑time, in‑person position based on the Pittsburgh campus. The start date will be Jan 2026 with flexibility.
Position 2: Research Technician
We are hiring a research technician to support our work on the heterogeneity of pollen phenology in the Pittsburgh area through expanded pollen sampling and high-resolution vegetation monitoring. The technician will lead or assist in deploying and maintaining airborne samplers, preparing pollen samples for analysis, operating UAV (drone) flights for vegetation monitoring, and data management. This position is well-suited for candidates with experience or strong interest in field ecology, environmental sampling, or remote sensing. There will be opportunities to contribute to manuscript preparation, develop interdisciplinary expertise in environmental data science, work closely with other lab members, and receive mentorship for future career goals in research or applied environmental science.
Preferred qualifications:
- Experience in field data collection, especially with ecological or environmental sampling
- Experience operating or interest in learning UAV systems for ecological research
- Attention to detail and strong organizational skills
- Interest in gaining experience with data processing and analysis tools (e.g., R, GIS) is a plus
- Valid driver’s license and willing to drive to field sites
This is a full‑time, in‑person position based on the Pittsburgh campus. The start date will be Summer 2026 with flexibility.
Position 3: PhD Student
We are recruiting a PhD student to develop research projects at the intersection of phenology, biodiversity, and global change, using large ecological datasets and innovative modeling approaches. Potential projects include:
A. Modeling seasonal changes in biodiversity (e.g., richness, evenness) along environmental gradients to improve our understanding of the biodiversity curve under environmental change and its link to phenology. This project will leverage data from large-scale observatory networks.
B. Forecasting fine-scale pollen concentrations in urban landscapes using models that integrate wind-pollinated plant composition and phenology. This project will leverage remote sensing imagery, ground observations, and air sampling data. The successful candidate will be involved in field sampling. C. Extracting phenological signals from multimodal data sources (e.g., herbarium specimens, social media, citizen science) to reconstruct and model phenological change across space and time.
The PhD student will co-develop research questions and methods with the PI, lead data analysis, collaborate with internal and external partners, prepare manuscripts, and present scientific findings. We welcome students trained in an ecology background who would like to develop expertise in ecological modeling and data science, as well as students who are passionate about applying statistical and computational methods to tackle challenges in global change biology.
Preferred qualifications:
- A background in ecology, environmental science, data science, or related fields
- Strong quantitative skills, or demonstrated ability and motivation to develop them further
- Curiosity about how environmental change (e.g., climate change, human modifications) is shaping ecosystems
This is a full‑time, in‑person position based on the Pittsburgh campus. The successful candidate will start in Fall 2026.
Why Join Us?
- Data-driven research: Our projects draw on diverse, large-scale datasets spanning remote sensing, ecological observatories, citizen science, and environmental sensors. Lab members will learn, apply, and develop advanced data science methods, such as Bayesian modeling and machine learning, to address pressing questions in global change biology.
- Interdisciplinary collaborations: Lab members will engage in collaborative research both within the lab and across a broad network of partners in ecology, evolution, statistics, public health, environmental economics, and more.
- Individualized mentorship: Lab members will receive dedicated meeting time and constructive, tailored feedback. Research projects will be co-developed to align with each member’s interests and long-term goals, whether focused on theory, methods, or applied questions. Training will be adapted to each member’s background, to support those transitioning between fields such as ecology and data science.
- Career development: Funded opportunities will be available for attending workshops and presenting at conferences. Members will receive structured support in leading publications, mentoring junior researchers, writing grant proposals, professional networking, and future job applications.
- Inclusive lab culture: We are committed to building a collaborative, inclusive, and diverse lab environment that supports the success of all members.
University, Department & Location
The University of Pittsburgh is a top-ranked public research university known for its strong commitment to interdisciplinary scholarship and societal impact. The Department of Biological Sciences is a vibrant and collaborative community spanning ecology and evolution, molecular biology, and neuroscience. It offers a supportive environment for cutting-edge research and graduate training. Located in the affordable and culturally rich city of Pittsburgh, the university is situated in a hub of green spaces, world-class museums, and a thriving tech and healthcare ecosystem. Pittsburgh is consistently ranked among the most livable cities in the U.S., with access to nature, diverse neighborhoods, and a strong sense of community.
How to Apply
Please send a brief cover letter (within one page), a CV, and an optional writing sample to YIS218@pitt.edu. Indicate in the subject line which position(s) you’re applying for, in the format of “[Your Last Name] – [Position] – Song Lab Recruitment.”
- Applications for the postdoc and technician positions will be reviewed on a rolling basis until filled.
- Prospective PhD students should reach out by Fall 2025 for admission in Fall 2026. Competitive applicants will be guided through the formal application process to the graduate program in Biological Sciences.
- I will be attending the upcoming ESA conference at Baltimore. Please feel free to reach out if you’d like to meet in person to discuss any of the positions.