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2 Found open positions

Post-Doctoral Research Fellow, Bayesian Methods for B Cell Receptor Sequence Lineages

FH Public Health Sciences Division
Category: Biostatistics, Bioinformatics and Computational Biology
US-WA-
Job ID: 18642

Overview

Cures Start Here. At Fred Hutchinson Cancer Research Center, home to three Nobel laureates, interdisciplinary teams of world-renowned scientists seek new and innovative ways to prevent, diagnose and treat cancer, HIV/AIDS and other life-threatening diseases. Fred Hutch’s pioneering work in bone marrow transplantation led to the development of immunotherapy, which harnesses the power of the immune system to treat cancer. An independent, nonprofit research institute based in Seattle, Fred Hutch houses the nation’s first cancer prevention research program, as well as the clinical coordinating center of the Women’s Health Initiative and the international headquarters of the HIV Vaccine Trials Network. Careers Start Here.

 

At Fred Hutch, we believe that the innovation, collaboration, and rigor that result from diversity and inclusion are critical to our mission of eliminating cancer and related diseases. We seek employees who bring different and innovative ways of seeing the world and solving problems. Fred Hutch is in pursuit of becoming an antiracist organization.  We are committed to ensuring that all candidates hired share our commitment to diversity, antiracism, and inclusion.   


 

Post-Doctoral Research Fellow/Research Associate - Postdoctoral position to develop Bayesian methods for B cell receptor sequence lineages

 

The goal of our project is to develop, implement, and apply Bayesian evolutionary algorithms for the analysis of B cell receptor sequence lineages. These lineages are important for understanding the events leading to the development of high-affinity antibodies.

 

We are motivated to:

  • use a Bayesian approach to appropriately account for uncertainty in phylogenetic inferences (which is considerable in this case)
  • fit and use complex models of somatic hypermutation and selection that violate the commonly-applied IID assumption in phylogenetics
  • develop efficient, elegant, and robust implementations of the newly developed methodology and make them available in open-source software for the community.

Responsibilities

We will work together to develop novel models, implement these models in open-source software, write tests to verify correctness, apply the methods to a variety of data sets, and write papers describing the results.

 

We’ll have the opportunity to work with a broad range of leading researchers, including:

  • biologists Jesse Bloom, Leslie Goo, Julie Overbaugh, Gabriel Victora, and their labs
  • statisticians Vladimir Minin, Noah Simon, Marc Suchard, and their groups.
     

Environment
The position will come with a competitive postdoc-level salary with great benefits for two years, with possibility of extension. The environment is lively yet casual, with a strong emphasis on collaborative work. The Center is housed in a lovely campus on Lake Union a short walk from downtown, and a slightly longer walk from the University of Washington. The Matsen group is in the newly-remodeled Steam Plant building overlooking the lake. Powerful computing resources and a helpful IT staff await. Ideally you’d want to be on campus (when that’s possible again) but long-term remote work is possible from these states: Alabama, Alaska, Arizona, California, Colorado, Hawaii, Idaho, Maryland, Minnesota, Montana, New York, Ohio, Oregon, South Carolina, and Texas.

 

We believe that science is for everyone. We have had researchers with a variety of backgrounds, including Latinx, Black, Asian, and Middle Eastern. We have had women, men, gay, and straight, and welcome people of all sexual orientations and gender identities. We have had successful high schoolers, postdocs, people who were the first in their family to attend college, and one who had decided that college wasn't for them. We have had researchers with backgrounds in biology, physics, statistics, math, and computer science.

 

We acknowledge the historical and present barriers for underrepresented groups, and work to increase diversity, equity and inclusion in computational biology. Members of underrepresented groups are especially encouraged to apply.

 

You can find out more about our group by visiting: 

http://matsen.fredhutch.org/
http://github.com/matsengrp

Qualifications

The ideal candidate for this project would have experience with the statistical underpinnings of Bayesian phylogenetic analysis, as well as experience implementing models in code. However, we welcome applications from candidates with less statistical expertise but a deep desire to expand their skills in this area. We hope applicants will want to improve their coding abilities through clean coding practices, code review, and a modern development workflow. The ideal candidate would also be motivated to improve biological understanding through computation, and so would be enthusiastic about working closely with our leading biologist collaborators.

 

MINIMUM QUALIFICATIONS:

  • Ph.D. in biology, computer science, math, or another relevant area
  • Solid foundation in Bayesian phylogenetics or other challenging Bayesian estimation problem
  • Computer programming experience
  • Clear ability to perform independent research
     

If you are interested in this position, please submit the following materials:

  • Two representative publications
  • A code sample
  • CV

 

A statement describing your commitment and contributions toward greater diversity, equity, inclusion, and antiracism in your career or that will be made through work at Fred Hutch is requested of all finalists.

Post-Doctoral Research Fellow, Computational Cancer Biology

FH Public Health Sciences Division
Category: Biostatistics, Bioinformatics and Computational Biology
Seattle, WA, US
Job ID: 18174

Overview

Cures Start Here. At Fred Hutchinson Cancer Research Center, home to three Nobel laureates, interdisciplinary teams of world-renowned scientists seek new and innovative ways to prevent, diagnose and treat cancer, HIV/AIDS and other life-threatening diseases. Fred Hutch’s pioneering work in bone marrow transplantation led to the development of immunotherapy, which harnesses the power of the immune system to treat cancer. An independent, nonprofit research institute based in Seattle, Fred Hutch houses the nation’s first cancer prevention research program, as well as the clinical coordinating center of the Women’s Health Initiative and the international headquarters of the HIV Vaccine Trials Network. Careers Start Here. 
 
At Fred Hutch, we believe that the innovation, collaboration, and rigor that result from diversity and inclusion are critical to our mission of eliminating cancer and related diseases. We seek employees who bring different and innovative ways of seeing the world and solving problems. Fred Hutch is in pursuit of becoming an antiracist organization. We are committed to ensuring that all candidates hired share our commitment to diversity, antiracism, and inclusion. 

 


 
The laboratory of Dr. Gavin Ha has a Post-Doctoral Research Fellow position open in the Computational Biology Program of the Public Health Sciences and Human Biology Divisions. We are seeking a highly motivated individual who is interested in developing and implementing innovative computational and analytical approaches to study the genetics and epigenetics of cancer. Candidates who are excited about large/complex ‘omics’ data analysis of cancer genomes, computational methods development, and “liquid biopsy” research are encouraged to apply. The position has a competitive salary with great benefits.  
 
Dr. Ha is a Prostate Cancer Foundation Young Investigator, V Foundation Scholar, and holds an NCI Transition Career Development Award. His laboratory develops computational approaches to study cancer genomes from tumors and liquid biopsies, such as circulating tumor DNA. See the lab websites for more information: https://gavinhalab.org/.   
 
We work in an interdisciplinary team environment with many local and external experts. All of our projects involve partnering with investigators who have diverse expertise in molecular and experimental biology, cancer biology, and clinical research. Potential projects will be part of collaborations with Dr. Peter Nelson (Director, Prostate Cancer Research Program, Fred Hutch), Dr. Andrew Hsieh (Deputy Director, Bladder Cancer Program, Fred Hutch), and investigators studying other cancers.  

Responsibilities

The successful candidate will have the opportunity to work on transformative and leading-edge research problems in cancer research:  

  • Cancer Genome Analysis – study tumor evolution, non-coding genome alterations, genome rearrangements and chromatin organization, cell plasticity, metastatic disease  
  • Liquid Biopsies – develop novel approaches to analyze circulating tumor DNA.  
  • Multi-omic Data integration – study of advanced bladder cancer    
  • Methods Development for New Technologies – linked-read or long-read genome sequencing of tumors.  
  • For examples of recent studies, see PMID:29909985PMID:29109393PMID:25060187

Qualifications

Applicants must have a PhD or MD (or equivalent) with training in one of these disciplines:  

  • Computational biology, bioinformatics, computer science, data science, statistics, computer/electrical engineering, physics, or other related fields.

 

Applicants should have some or all of the following skills and experience:  

  • Work well in team environments, have strong communication/organization skills and is detail-oriented   
  • Highly motivated individual who think independently but also enjoy working in a dynamic, collaborative, multidisciplinary team  
  • Strong programming experience (R, Python, Matlab, Java, C/C++, Perl or other languages for research)  
  • Experience with cancer genome data analysis is considered a strong asset  
  • A background in cancer biology (especially in prostate) is considered a strong asset.  
  • Experience with analyzing sequencing data is considered a strong asset  
  • Experience with high performance computing environments and cloud computing environments is a plus 
  • Applicants must have a demonstrated publication track record  

 

Candidates with strong interest and/or expertise in any of these research areas are highly encouraged to apply:  

  • Cancer genomics, liquid biopsies, tumor evolution/heterogeneity  
  • Application of statistical modeling, algorithm design, machine learning to study cancer and genetics  
  • Analysis of large, complex genome, epigenome, and transcriptome data 

 

To apply, please submit your application with the following:  

  • A several paragraph statement of research interests  
  • CV 
  • Names and email addresses of three references 
  • Two representative publications or preprints (if available)  

  
A statement describing your commitment and contributions toward greater diversity, equity, inclusion, and anti-racism in your career or that will be made through work at Fred Hutch is requested of all finalists. 

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