Jing receives R01 Award
26 Sep 2022 by Jing Ma

Jing received an R01 award from the National Institute of General Medical Sciences for the project on “Statistical Methods for Network-based Integrative Analysis of Microbiome Data”.

This project is in collaboration with Drs. Ali Shojaie, Yue Wang, and Robert Kaplan.

Jing receives Translational Data Science Pilot Award
15 Sep 2022 by Jing Ma

Jing received an award from The Translational Data Science Integrated Research Center for the pilot project on “Systems biology analysis of the immunomodulatory influence of circulating gut microbe-derived metabolites after transplantation”.

This project is in collaboration with Dr. Kate Markey, and will analyze a novel blood sample-derived data set. Collected from patients who underwent allogeneic stem cell transplantation, these samples have already been analyzed using state of the art flow cytometry and metabolomics methods. We now aim to a) develop new understanding of the links between microbial metabolites and immune function, and b) develop novel computational approaches to analyze these types of data sets.

Kun Yue receives Best Student Paper Award
28 Jul 2021 by Jing Ma

Congratulations to Kun Yue, who has been named a winner of Best Student Paper for the 2021 WNAR Student Paper Competition!

Her paper “REHE: Fast Variance Components Estimation for Linear Mixed Models” proposes a new method for estimating the variance components in linear mixed models.

Jing receives Microbiome Research Pilot Award
02 Jul 2021 by Jing Ma

Jing received an award from The Pathogen Associated Malignancies Integrated Research Center for the pilot project on “Statistical Methods for Network-based Analysis of the Colorectal Cancer Microbiome”.

This project is in collaboration with Dr. Amanda Phipps (associate professor of epidemiology, University of Washington, and associate professor in the Public Health Sciences Division), Dr. Sam Minot (associate director of data science applications, Hutch Data Core) and Dr. Neelendu Dey (assistant professor in the Clinical Research Division).

Ilias Moysidis joins the group
21 Jun 2021 by Jing Ma

Ilias Moysidis obtained his Ph.D. in Statistics from Penn State University in 2021. Welcome, Ilias!

Postdoc Yue Wang joins ASU
15 Aug 2020 by Jing Ma

Congratulations, Yue! Yue has done amazing work in dimensionality reduction of structured microbiome data and high-dimensional inference. Check out his paper here and here.

Launch of the Dog Aging Project
20 Nov 2019 by Jing Ma

We are looking for dogs for the largest-ever study of aging in canines! You can find out more about the Dog Aging Project here or from this article in New York Times.

Jing will visit Texas A&M Statistics
05 Aug 2019 by Jing Ma

I will be visiting Department of Statistics at Texas A&M University as Assistant Professor, during the academic year 2019-2020.

Machine learning helps elucidate chronic kidney disease progression
20 May 2019 by Jing Ma

Joint work with Drs. Alla Karnovsky, Farsad Afshinnia and George Michailidis on differential network enrichment analysis is featured at Fred Hutch Science Spotlight.

Jing receives the Jayne Koskinas Ted Giovanis Foundation Award
25 Jul 2018 by Jing Ma

Jing received award from The Jayne Koskinas Ted Giovanis Foundation for Health and Policy, joint with Minjoung Kyoung, Michael Konopka, Tara Sigdel, Young Hwan Chang on a proposal titled ``Understanding Therapeutics Failures Through 4D Single-cell Analysis of Metabolic Heterogeneity”.

Application for postdoc is closed
16 Feb 2018 by Jing Ma

Position Title: Postdoctoral Researcher in Biostatistics

Summary: The research group led by Dr. Jing Ma in the Division of Public Health Sciences at Fred Hutchinson Cancer Research Center and Prof. Ali Shojaie in the Department of Biostatistics at the University of Washington is seeking for a highly motivated postdoctoral researcher to develop novel statistical methods for problems in genomics and microbiome. The project will focus on methods for analysis of complex biological/ecological systems using novel statistical machine learning tools, including network analysis, high-dimensional regression and inference. This is a unique opportunity for someone who is interested in a collaborative environment and interacting with investigators with diverse experiences. The position is available for 2 years from August 1st 2018 (or by negotiation).

Duties and Responsibilities: The successful candidate will work with Dr. Jing Ma and Prof. Ali Shojaie in developing novel statistical/computational methods in the context of genomics and microbiome. He/she will have opportunities to join collaborative research projects within Fred Hutch and UW as well as external collaborations.

Position Qualifications: The successful candidate will have

  • completed (or nearly completed) a PhD in Statistics/Biostatistics or a closely related area prior to their appointment;
  • demonstrated a capacity to produce high quality research.

In addition, the ideal candidate will also have

  • expertise in statistical machine learning and high-dimensional inference;
  • applied work in genomics and microbiome data analysis.

Salary Range: Competitive.

How to Apply: Please email the following materials to jingma@fredhutch.org:

  • CV;
  • two publication samples or preprints;
  • a one page statement of research interests;
  • contact information of three references.

Application is closed.

Save the date: 2018 Fred Hutch Microbiome Symposium
25 Oct 2017 by Jing Ma

Fred Hutch is excited to host the 2018 Microbiome Symposium on March 16th, 2018! Sessons include

  • Making sense of the human microbiome,
  • Microbiome and infectious disease,
  • Bioinformatics for the microbiome,
  • Microbiome data analysis.
Jing will join Fred Hutch Biostatistics
05 Jul 2017 by Jing Ma

Jing will join Biostatistics within Division of Public Health Sciences as Assistant Professor, starting from August 1st, 2017.