Post Doc - Open Rank

We are looking for a motivated postdoctoral research fellow to join our computational
lab to infer and interpret gene regulatory networks from single-cell and spatiotemporal
multiomic datasets at the University of Massachusetts Chan Medical School.

About the Lab:

Our computational lab was opened in October 2023, dedicated to developing novel
methods for inferring and analyzing gene regulatory networks. We primarily use single-cell
and spatiotemporal multiomic datasets to uncover causal gene regulations. We encourage
lab members to pursue their own ideas that align with the lab's overall research goals. The
lab is committed to supporting career development, such as conference participation and
hybrid working arrangements. We particularly welcome people from diverse disciplines,
cultures, countries, and underrepresented minority groups.

About the Department:

The Department of Genomics and Computational Biology at UMass Chan Medical School,
located in the state-of-the-art Albert Sherman Center, is a forefront of research in
Computational Biology, Evolutionary Biology, and Genomics. The Department focuses on
deciphering complex biological data using computational and genomic methods. Key
research areas include regulatory mechanisms in mammalian evolution, the interplay
between genetics and epigenetics in human health, and genetic diversity in disease
susceptibility and treatment responses. The Department is committed to an inclusive,
collaborative environment, integrating with adjacent departments and benefiting from
shared cutting-edge facilities. This synergy, along with advanced computing and
experimental resources, propels the Department's exploration of molecular, cellular, and
evolutionary mechanisms in health and disease

The responsibilities include:

* Develop accurate and efficient computational methods to infer causal gene
regulatory networks from diverse single-cell and spatiotemporal multiomic data
* Evaluate and compare these methods with existing approaches
* Apply these methods to generate new biological insights
* Implement and maintain these methods as user-friendly software packages
* Disseminate these methods with written manuscripts and academic presentations

We seek postdoctoral researchers with:

* PhD degree in a quantitative field such as mathematics, statistics, physics, computer
science, electrical engineering, computational biology, bioinformatics, biostatistics,
and genetics
* Proficient in at least one modern programming language such as Python, Julia, and R
* Strong interest in gene regulatory network or causal inference
* Ability to work independently and as part of a team
* A track record of publications in peer-reviewed journals
* Biomedical background not required

The following is considered a plus:

* Experience in network inference, causal inference, network science, algorithm,
genome-wide association studies, Mendelian randomization, and/or dynamical
systems
* Experience in computational and statistical method development in any discipline
* Experience working with single-cell, bulk sequencing, or other biological data
Good practice in software development
* Strong communication skills

TO APPLY: Please email a cover letter, your resume, and your references/recommendation letters to Dr. Wang: Lingfei.wang@umassmed.edu