UMass Med School
Post Doc - Open Rank
UMass Med School, Worcester, Massachusetts, us, 01609
Post Doc - Open Rank
Minimum Salary
US-MA-Worcester
Job Location
2 months ago (7/16/2024 1:59 PM)
Requisition Number
2024-45612
# of Openings
1
Posted Date
Day
Shift
Exempt
Exempt/Non-Exempt Status
Non Union Position-W63-Residents/Post Docs
Overview
We are looking for a motivated postdoctoral research fellow to join our computationallab to infer and interpret gene regulatory networks from single-cell and spatiotemporalmultiomic datasets at the University of Massachusetts Chan Medical School.About the Lab:
Our computational lab was opened in October 2023, dedicated to developing novelmethods for inferring and analyzing gene regulatory networks. We primarily use single-celland spatiotemporal multiomic datasets to uncover causal gene regulations. We encouragelab members to pursue their own ideas that align with the lab's overall research goals. Thelab is committed to supporting career development, such as conference participation andhybrid 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 inComputational Biology, Evolutionary Biology, and Genomics. The Department focuses ondeciphering complex biological data using computational and genomic methods. Keyresearch areas include regulatory mechanisms in mammalian evolution, the interplaybetween genetics and epigenetics in human health, and genetic diversity in diseasesusceptibility and treatment responses. The Department is committed to an inclusive,collaborative environment, integrating with adjacent departments and benefiting fromshared cutting-edge facilities. This synergy, along with advanced computing andexperimental resources, propels the Department's exploration of molecular, cellular, andevolutionary mechanisms in health and disease
Responsibilities
The responsibilities include:
* Develop accurate and efficient computational methods to infer causal generegulatory 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
Qualifications
We seek postdoctoral researchers with:
* PhD degree in a quantitative field such as mathematics, statistics, physics, computerscience, 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 dynamicalsystems* Experience in computational and statistical method development in any discipline* Experience working with single-cell, bulk sequencing, or other biological dataGood practice in software development* Strong communication skillsTO APPLY: Please email a cover letter, your resume, and your references/recommendation letters to Dr. Wang: Lingfei.wang@umassmed.edu
#J-18808-Ljbffr
Minimum Salary
US-MA-Worcester
Job Location
2 months ago (7/16/2024 1:59 PM)
Requisition Number
2024-45612
# of Openings
1
Posted Date
Day
Shift
Exempt
Exempt/Non-Exempt Status
Non Union Position-W63-Residents/Post Docs
Overview
We are looking for a motivated postdoctoral research fellow to join our computationallab to infer and interpret gene regulatory networks from single-cell and spatiotemporalmultiomic datasets at the University of Massachusetts Chan Medical School.About the Lab:
Our computational lab was opened in October 2023, dedicated to developing novelmethods for inferring and analyzing gene regulatory networks. We primarily use single-celland spatiotemporal multiomic datasets to uncover causal gene regulations. We encouragelab members to pursue their own ideas that align with the lab's overall research goals. Thelab is committed to supporting career development, such as conference participation andhybrid 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 inComputational Biology, Evolutionary Biology, and Genomics. The Department focuses ondeciphering complex biological data using computational and genomic methods. Keyresearch areas include regulatory mechanisms in mammalian evolution, the interplaybetween genetics and epigenetics in human health, and genetic diversity in diseasesusceptibility and treatment responses. The Department is committed to an inclusive,collaborative environment, integrating with adjacent departments and benefiting fromshared cutting-edge facilities. This synergy, along with advanced computing andexperimental resources, propels the Department's exploration of molecular, cellular, andevolutionary mechanisms in health and disease
Responsibilities
The responsibilities include:
* Develop accurate and efficient computational methods to infer causal generegulatory 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
Qualifications
We seek postdoctoral researchers with:
* PhD degree in a quantitative field such as mathematics, statistics, physics, computerscience, 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 dynamicalsystems* Experience in computational and statistical method development in any discipline* Experience working with single-cell, bulk sequencing, or other biological dataGood practice in software development* Strong communication skillsTO APPLY: Please email a cover letter, your resume, and your references/recommendation letters to Dr. Wang: Lingfei.wang@umassmed.edu
#J-18808-Ljbffr