The Statistics Identity Crisis: Am I a Data Scientist
30 Oct 2015The joint ASA/Simply Statistics webinar on the statistics identity crisis is now live!
Follow us on twitter @simplystats
Follow us on twitter @simplystats
The joint ASA/Simply Statistics webinar on the statistics identity crisis is now live!
It’s pretty exciting to be in genomics at Hopkins right now with three new Bloomberg professors in genomics areas, a ton of stellar junior faculty, and a really fun group of students/postdocs. If you want to get in on the action here is a non-comprehensive list of great opportunities.
Job: Multiple tenure track faculty positions in all areas including in genomics
Department: Biostatistics
To apply: http://www.jhsph.edu/departments/biostatistics/_docs/faculty-ad-2016-combined-large-final.pdf
Deadline: Review ongoing
Job: Tenure track position in data intensive biology
Department: Biology
To apply: http://apply.interfolio.com/31146
Deadline: Nov 1st and ongoing
Job: Tenure track positions in bioinformatics, with focus on proteomics or sequencing data analysis
Department: Oncology Biostatistics
To apply: https://www.research-it.onc.jhmi.edu/DBB/PhD_Statistician.pdf
Deadline: Review ongoing
Job: Postdoc(s) in statistical methods/software development for RNA-seq
Employer: Jeff Leek
To apply: email Jeff (http://jtleek.com/jobs/)
Deadline: Review ongoing
Job: Data scientist for integrative genomics in the human brain (MS/PhD)
Employer: Andrew Jaffe
To apply: email Andrew (http://www.aejaffe.com/jobs.html)
Deadline: Review ongoing
Job: Research associate for genomic data processing and analysis (BA+)
Employer: Andrew Jaffe
To apply: email Andrew (http://www.aejaffe.com/jobs.html)
Deadline: Review ongoing
Job: PhD developing scalable software and algorithms for analyzing sequencing data
Employer: Ben Langmead
To apply: http://www.cs.jhu.edu/graduate-studies/phd-program/
Deadline: See site
Job: Postdoctoral researcher developing scalable software and algorithms for analyzing sequencing data
Employer: Ben Langmead
To apply: email Ben (http://www.langmead-lab.org/open-positions/)
Deadline: Review ongoing
Job: Postdoctoral researcher developing algorithms for challenging problems in large-scale genomics whole-genome assenbly, RNA-seq analysis, and microbiome analysis
Employer: Steven Salzberg
To apply: email Steven (http://salzberg-lab.org/)
Deadline: Review ongoing
Job: Research associate for genomic data processing and analysis (BA+) in cancer
Employer: Luigi Marchionni (with Don Geman)
To apply: email Luigi (http://luigimarchionni.org/)
Deadline: Review ongoing
Job: Postdoctoral researcher developing algorithms for biomarkers development and precision medicine application in cancer
Employer: Luigi Marchionni (with Don Geman)
To apply: email Luigi (http://luigimarchionni.org/)
Deadline: Review ongoing
Job:Postdoctoral researcher developing methods in machine learning, genomics, and regulatory variation
Employer: Alexis Battle
To apply: email Alexis (http://battlelab.jhu.edu/join_us.html)
Deadline: Review ongoing
Job: Postdoctoral fellow with interests in biomarker discovery for Alzheimer’s disease
Employer: Madhav Thambisetty / Ingo Ruczinski
To apply: http://www.alzforum.org/jobs/postdoctoral-research-fellow-alzheimers-disease-biomarkers
Deadline: Review ongoing
Job: Postdoctoral positions for research in the interface of statistical genetics, precision medicine and big data
Employer: Nilanjan Chatterjee
To apply: http://www.jhsph.edu/departments/biostatistics/_docs/postdoc-ad-chatterjee.pdf
Deadline: Review ongoing
Job: Postdoctoral research developing algorithms and software for time course pattern detection in genomics data
Employer: Elana Fertig
To apply: email Elana (ejfertig@jhmi.edu)
Deadline: Review ongoing
Job: Postdoctoral fellow to develop novel methods for large-scale DNA and RNA sequence analysis related to human and/or plant genetics, such as developing methods for discovering structural variations in cancer or for assembling and analyzing large complex plant genomes.
Employer: Mike Schatz
To apply: email Mike (http://schatzlab.cshl.edu/apply/)
Deadline: Review ongoing
We are all always on the hunt for good Ph.D. students. At Hopkins students are admitted to specific departments. So if you find a faculty member you want to work with, you can apply to their department. Here are the application details for the various departments admitting students to work on genomics: https://ccb.jhu.edu/students.shtml
Tl;dr: We will host a Google Hangout of our popular JSM session October 30th 2-4 PM EST.
I organized a session at JSM 2015 called “The statistics identity crisis: am I really a data scientist?” The session turned out to be pretty popular:
Packed room of statisticians with identity crises at #JSM2015 session: are we really data scientists? pic.twitter.com/eLsGosoTCt
— Dr Ruth Etzioni (@retzioni) August 11, 2015
but it turns out not everyone fit in the room:
This is the closest I can get to @statpumpkin's talk. #jsm2015 still had no clue how to predict session attendance. pic.twitter.com/gTb4OqdAo3
— sandy griffith (@sgrifter) August 11, 2015
Thankfully, Steve Pierson at the ASA had the awesome idea to re-run the session for people who couldn’t be there. So we will be hosting a Google Hangout with the following talks:
| 'Am I a Data Scientist?': The Applied Statistics Student's Identity Crisis — Alyssa Frazee, Stripe | |
| How Industry Views Data Science Education in Statistics Departments — Chris Volinsky, AT&T | |
| Evaluating Data Science Contributions in Teaching and Research — Lance Waller, Emory University | |
| Teach Data Science and They Will Come — Jennifer Bryan, The University of British Columbia |
You can watch it on Youtube or Google Plus. Here is the link:
https://plus.google.com/events/chuviltukohj2inbqueap9h7228
The session will be held October 30th (tomorrow!) from 2-4PM EST. You can watch it live and discuss the talks using the hashtag [
Tl;dr: We will host a Google Hangout of our popular JSM session October 30th 2-4 PM EST.
I organized a session at JSM 2015 called “The statistics identity crisis: am I really a data scientist?” The session turned out to be pretty popular:
Packed room of statisticians with identity crises at #JSM2015 session: are we really data scientists? pic.twitter.com/eLsGosoTCt
— Dr Ruth Etzioni (@retzioni) August 11, 2015
but it turns out not everyone fit in the room:
This is the closest I can get to @statpumpkin's talk. #jsm2015 still had no clue how to predict session attendance. pic.twitter.com/gTb4OqdAo3
— sandy griffith (@sgrifter) August 11, 2015
Thankfully, Steve Pierson at the ASA had the awesome idea to re-run the session for people who couldn’t be there. So we will be hosting a Google Hangout with the following talks:
| 'Am I a Data Scientist?': The Applied Statistics Student's Identity Crisis — Alyssa Frazee, Stripe | |
| How Industry Views Data Science Education in Statistics Departments — Chris Volinsky, AT&T | |
| Evaluating Data Science Contributions in Teaching and Research — Lance Waller, Emory University | |
| Teach Data Science and They Will Come — Jennifer Bryan, The University of British Columbia |
You can watch it on Youtube or Google Plus. Here is the link:
https://plus.google.com/events/chuviltukohj2inbqueap9h7228
The session will be held October 30th (tomorrow!) from 2-4PM EST. You can watch it live and discuss the talks using the hashtag](https://twitter.com/search?q=%23jsm2015) or you can watch later as the video will remain on Youtube.
Theranos is a Silicon Valley diagnostic testing company that has been in the news recently. The story of Theranos has fascinated me because I think it represents a perfect collision of the tech startup culture and the health care culture and how combining them together can generate unique problems.
I talked with Elizabeth Matsui, a Professor of Pediatrics in the Division of Allergy and Immunology here at Johns Hopkins, to discuss Theranos, the realities of diagnostic testing, and the unique challenges that a health-tech startup faces with respect to doing good science and building products people want to buy.
Notes:
I just uploaded Episode 3 of Not So Standard Deviations so check your feeds. In this episode Hilary and I talk about our jobs and the life of the data scientist in both academia and the tech industry. It turns out that they’re not as different as I would have thought.