Physical Scientist at UW Climate Impacts Group

Written by

The Climate Impacts Group (CIG) at the University of Washington is hiring! Keep your eyes peeled for multiple opportunities to join our team in the coming weeks and months.

Our first need is for a physical scientist to join our team of professional researchers devoted to use-inspired research. We are looking for a person with strong technical skills in manipulating climate model data, interpreting hydrological and meteorological data, and physical process modelling. This position is intended to support the CIG’s senior research staff in work coproduced with our local, state, federal and tribal partners. The CIG is a fast-paced, dynamic, and deadline driven environment, which requires the research scientist to bring strong organizational and project management skills as well as problem-solving and priority-setting abilities.

While we are open to applicants with at least 2 years of experience and a B.S. in computer science, mathematics, engineering, earth sciences or a related field, we would prefer a candidate with more experience (Master’s or PhD). This is a full-time staff scientist research position with no teaching expectations and no path to University tenure. For more details and to apply, go to this link.

Contact: Jason Vogel, jmvogel@uw.edu

eScience Institute Seminar: Joe Hamman, National Center for Atmospheric Research

Written by

“Enabling science using open source software, big data platforms, and diverse communities; applications in climate and hydrologic research”

Please join the UW eScience Institute for a special guest seminar by Joe Hamman of the National Center for Atmospheric Research!

When: Thursday, September 19, 3:00 pm – 4:00 pm

Where: WRF Data Science Studio, 6th Floor, Physics/Astronomy Tower

Abstract: Across many data-driven fields, the abundance of data and compute is offering researchers exciting opportunities for scientific discovery. Realizing these discoveries is, however, often impeded by unnecessary constraints on the research process. These constraints stem from a variety of sources, including the complexities of working with very large datasets, and the failure to follow best data science practices. In this talk, I will discuss how open source software, big data platforms, and vibrant and diverse communities are enabling a new paradigm of scientific research. We will explore how this new paradigm is enabling open science and scientific transparency in service of society. I will provide examples from the perspective of climate and hydrologic modeling, demonstrating how pressing challenges in these domains are being addressed through the community development of open software and infrastructure through the Pangeo Project. I will end by highlighting areas in the climate and hydrologic modeling domains where emerging data science methods are likely to play an important role in the research landscape in the coming years.

Bio: Joseph Hamman is a scientist at the National Center for Atmospheric Research (NCAR). He received a PhD in Civil and Environmental Engineering from the University of Washington (2016) and additional postdoctoral training in computational hydrology at NCAR (2016-2018). His work focuses on using emerging data sciences approaches in service of climate and hydrologic modeling research. He has made significant contributions to open source scientific software projects (e.g. Xarray, Dask, Jupyter) and helps lead the Pangeo Project – a community effort for big data in the geosciences.

Software Carpentry Workshop

Written by

The Carpentries is a non-profit volunteer organization whose members teach researchers how to use computing tools and tools for management, analysis and visualization of data.

Software Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

Who: The course is aimed at graduate students and other researchers. You don’t need to have any previous knowledge of the tools that will be presented at the workshop.

Where: WRF Data Science Studio, 6th floor Physics/Astronomy Tower, University of Washington, 3910 15th Ave NE, Seattle, WA, 98105.

When: October 1st – 4th, 2019.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed, including the Bash shell, Git, a text editor like nano or BBEdit, and Python.

Code of Conduct: Everyone who participates in Carpentries activities is required to conform to the Code of Conduct. This document also outlines how to report an incident if needed.

Accessibility: We are committed to making this workshop accessible to everybody. The workshop organizers have checked that:

  • The room is wheelchair / scooter accessible.
  • Accessible restrooms are available.

Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.

Contact: Please email arokem@uw.edu for more information.

More Details & Registration

UW APL Open-Source Software Research Technician

Written by

The University of Washington’s Applied Physics Laboratory is looking for a research technician to assist with the development of open-source software tools in the geosciences. This is a part-time, temporary position with the possibility of extension after the first year depending on the availability of funds.

The project: NASA is funding us to test and deploy Pangeo, a community platform for Big Data geoscience, as a prototype to enable transition of scientific workflows to a cloud environment. See http://pangeo.io for more information.

The team: we are a small team of research scientists (climatology, hydrology, glaciology, volcanology), technicians and data science experts in academia and industry. We collaborate via in person meetings, Slack and GitHub. We stay connected with a global Pangeo community.

The work: many of the core tools for deploying Pangeo are in place. Now, we need help with developing scientific use cases that make full use of Pangeo’s parallel workflow capabilities, connecting Pangeo tools to existing NASA products, and helping educate scientists in using these tools.

Education and background: Minimum two years Bachelor’s level training in computer science, data science, and/or a domain scientist with demonstrated data science skills. Required experience with Python, Jupyter, Linux and GitHub; desirable experience with AWS, Kubernetes and satellite imagery applications.

Location: The team is distributed across multiple locations. The core team at the University of Washington is affiliated with the eScience Institute, where much of the work occurs. There may be opportunities for telecommuting.

Opportunities: We are committed to building an open and inclusive community that is dedicated to principles of reproducible science. We foster opportunities for professional development and immersion in leading edge data science tools.

Contact us: for more information e-mail Anthony Arendt, arendta@uw.edu.

Data Science Software Carpentry Workshop

Written by

Water data fans and foes,

Are you the data rockstar that you want to be? Do you want to spend less time coding and wrestling data and more time on research?

The eScience Institute is holding a Software Carpentry workshop on July 15-18 (9 AM – noon each day) in the WRF Data Science Studio. The Carpentries is a non-profit volunteer organization whose members teach researchers how to use computing tools and tools for management, analysis and visualization of data

The workshop focuses on software tools to make researchers more effective, allowing them to automate research tasks, automatically track their research over time, and use programming in Python to accelerate their research, and make it more reproducible.

More Details & Registration

Email Sarah Stone (sstone3@uw.edu) or Ariel Rokem (arokem@uw.edu) with any questions about the workshop.

Participants Reflect on First Waterhackweek

Written by

FWI and the UW eScience institute hosted the first Waterhackweek, a five-day collaborative event for freshwater-related data science, March 25 – 29, 2019. We asked participants to give us their insight on the event — here are their thoughts.

Zahra Sharifnezhadazizi
Zahra Sharifnezhadazizi, City College of New York

Zahra Sharifnezhadazizi, PhD candidate, The City College of New York

I am pursuing a doctorate in environmental engineering at City College of New York (CCNY) where I am working on satellite remote sensing data analysis for environmental purposes. The main focus of my current research is remote sensing analysis of Land Surface Emissivity with high spatial and temporal resolution which makes me handling a huge volume of data using MATLAB. In order to be able to apply novel data analytics, I started to attend the CUAHSI Cyberseminar Series which introduced me to new horizons of data analysis with Python.

Honestly, I simply imagined that it would be one of those boring compact lectures in a few sessions. However, later events brought me a completely different view. At first, it motivated me to start a three-week online Python course. Then, I went on with the webinars and became familiar with all sets of new tools and websites such as Hydroshare workflow, Jupyter notebook, GitHub online version control, Google Earth Engine, and GeoPandas.

In the workshop week, we continued on those materials in detail and had a hands-on project. The final project was set up in a way that each person in each group, took part in their own personal interest and ability. There was no peer pressure of being obliged to do something for the sake of not just being left behind. Even the title of the projects was chosen by each group which made us start collaboration and negotiation from a smaller society.

The major interesting point for me was that the instructors were ranged from professors to students. In addition, the workshop had various types of participants, from undergrads to faculty members. Therefore, I thought I could also be an instructor if I have anything special to contribute.

Apart from that, the diverse milieu of the workshop in both terms of culture and science, and the welcoming nature of Seattle let me have this notion that organizers are not only proficient in technology, but also experts in social sciences. To my mind, Waterhackweek 2019 was an amalgamation of innovation, expression, learning, friendship, and joy, and I would be delighted to be part of this community once again.

Zhen Han
Zhen Han, Big Water Consultants

Zhen Han, Data Reporting and Analytics Manager, Big Water Consultants

I had a wonderful time at the Waterhackweek. Within five days, I was able to pick up a lot of new data science techniques and directly apply those skills through hands-on project work. The instructors and organizations clearly put a lot of thoughts on the structure of the events to strike a balance between learning sections and project time.

Although there are a lot of contents to learn and practice within a short period of time, the learning environment during the hack week was extremely friendly and low-stress. I appreciate that at the onset of the event, all participants were reminded to get prepared to feel a little bit at loss, stay open-hearted to seek help and help each out, and appreciate the diversity of the participants.

The weekly one-hour cyber-seminars were great lead-ins for the hack week. It was great that we could get an overview of the contents and start to implement the tools before the event started. The learning sessions during the week were also well-structured and greatly expanded my horizon on tools and techniques for data science and water research.

More importantly, it was great to get exposure to a variety of projects and work in a diverse team on a hands-on project. My teammates came from consulting firms, academia, government, and non-government organizations. Everyone brought their own experience into the discussion and problem-solving process. I felt extremely grateful for the opportunity to learn from our team leads and my teammates.

Katya Cherukumilli
Katya Cherukumilli, University of Washington

Katya Cherukumilli, postdoctoral researcher, University of Washington

I am a postdoctoral researcher in Environmental Engineering at the UW and the founder and CEO of a nonprofit called Global Water Labs. My research focus is on the design and deployment of low-cost technologies for drinking water treatment in resource-constrained regions. My expertise is in analytical aquatic chemistry, material characterization, groundwater geochemistry, field-relevant technology design, and social entrepreneurship.

I do not have formal training in data science or programming but was recently introduced to Python and R/ggplot. So when I first heard the announcement for proposing projects for Waterhackweek (WHW), I was a bit hesitant because I thought that I did not think I had the adequate data science skillset to participate. However, having completed my first WHW experience, I am so happy that I did. I would recommend the experience to anyone who has a general interest in learning more about how data science skills can be applied to their research.

I had the privilege of leading a team of data scientists to work towards a common goal: to build a “map app” that visualized multiple groundwater contaminants, with the added user-friendly features of observing trends over time and space (including depth). This experience gave me a brief insight into the vast power of numerous tools and software packages, including Hydroshare, GitHub, Tethys, Google Earth Engine, and GeoPandas. It also taught me about the concepts of workflow, database wrangling/cleaning, and version control. These concepts, although quite rudimentary to experienced data scientists, were novel to an experimentalist like me.

Learning these concepts taught me how to do very interdisciplinary and highly productive collaborative research in a short period of time. Overall, through this experience, I was introduced to a unique and powerful network of data scientists passionate about water issues. I was also encouraged (and supported) to push my own intellectual boundaries and to learn new methods that will greatly contribute to my future research and humanitarian work.

Freshwater Initiative, eScience Institute Host First Waterhackweek

Written by

Waterhackweek 2019 participants at Portage Bay
Waterhackweek 2019 participants at Portage Bay (Robin Brooks / UW eScience Institute)

The UW Freshwater Initiative hosted the first Waterhackweek in partnership with the UW eScience Institute March 25 – 29, 2019 at the University of Washington (UW). At Waterhackweek, a five-day collaborative event for freshwater-related data science, water scientists from UW, other US and international universities, industry, and state departments learned about open-source technology, models, and data for conducting state-of-the-art research.

Waterhackweek participants at the opening reception
Waterhackweek participants at the opening reception (Yifan Cheng / UW Freshwater Initiative)

The hackweek model has emerged within the data science community as a powerful tool for fostering exchange of ideas in research and computation by providing training in modern data analysis workflows. In contrast to conventional academic conferences or workshops, hackweeks are intensive and interactive, facilitated by three core components: tutorials on state-of-the-art methodology, peer-learning, and on-site project work in a collaborative environment.This setup is particularly powerful for sciences that require not only domain-specific knowledge, but also effective computational workflows to foster rapid exchange of ideas and make discovery, as has been shown by the success of the previous eScience hackweeks. This is an excellent match with the nature of freshwater research where issues are sizeable and complicated and the community is diverse and synergistic.

Mornings consisted of interactive lectures, while afternoon sessions involved exploration of datasets and hands-on software development through project work in groups of four to eight people. During morning tutorial sessions, participants learned about state-of-the-art data science tools and workflows in interactive lectures covering techniques like accessing and formatting hydrometeorological datasets, leveraging community water data services, visualization, cloud computing, machine learning, Google Earth Engine, and practices for reproducible science.

Participants enjoy a Waterhackweek presentation
Participants enjoy a Waterhackweek presentation (Yifan Cheng / UW Freshwater Initiative)

On the first day of the event, interested participants were given the chance to pitch a project idea to the rest of the group. Their peers then decided which project they would like to “hack” on for the rest the week, and joined the project leaders to form project teams. Each afternoon, those small groups worked to define, clarify, and tackle different challenges in water sciences. The selected topics covered a broad spectrum of regions and subject matter, from the arid Southwest U.S. to tropical Hawaii and from Amazonian rivers to Alaskan lakes.

The teams used a diverse array of technologies to approach their chosen problems. One team explored the possibility of using a Raspberry Pi to collect and distribute water quality information during natural disasters. Another group used Google Earth Engine to model the complex dynamics of wildfire, vegetation change, surface water, and carbon release. Yet another team used Python data science and mapping libraries to visualize groundwater contaminants in California, while Conrad Koziol (Inlet Labs) and his team projected the future hydrology of the Pacific Northwest.

Explore the projects on GitHub

As part of the event, Waterhackweek participants, industry professionals, and members of the greater Freshwater Initiative and eScience Institute communities also attended Thursday evening’s Waterhackweek Community Mixer. Special guest speaker Sally Jewell, former U.S. Secretary of the Interior under President Barack Obama and former CEO of REI, discussed her experiences in understanding and managing water resources for the benefit of society. Waterhackweek 2019 participants also described their innovative new research in 90-second lightning talks and networked with experts in the freshwater and data science communities.

Special guest Sally Jewell speaking at the Waterhackweek Community Mixer
Special guest Sally Jewell speaking at the Waterhackweek Community Mixer (Yifan Cheng / UW Freshwater Initiative)

Thanks to our 2019 Waterhackweek organizers, including Nicoleta Cristea, Christina Bandaragoda, Anthony Arendt, Veronica Smith, Lillian McGill, Jacob Deppen, Owen Freed, Madhavi Srinivasan, and Rachael Murray.

The next Waterhackweek will take place March 23 – 27, 2020. Applications will open in August 2019 — stay tuned!

2019 ESIP Summer Meeting

Written by

Data in Action: Increasing the Use and Value of Earth Science Data and Information

For 20 years, ESIP meetings have brought together the most innovative thinkers and leaders around Earth observation data, thus forming a community dedicated to making Earth observations more discoverable, accessible and useful to researchers, practitioners, policymakers, and the public.
The week is sure to be filled with a number of exciting plenary talks, breakout sessions, posters, and more.

Dates: Tuesday, July 16th – Friday, July 19th, 2019 (ending after lunch), side meetings on 7/15.
Theme: Data in Action: Increasing the Use and Value of Earth Science Data and Information.
Call for Sessions: PROPOSE A SESSION here by April 26th, 2019.

Meeting Location: Greater Tacoma Convention Center, 1500 Commerce St, Tacoma, WA 98402

Lodging: The official hotel of the meeting is Hotel Murano, located at 1320 Broadway, Tacoma, WA 98402. The group rate is $121 per night. Online and phone reservations will be accepted until June 17, 2019. To make online reservations, click here. You may also make reservations by phone at 253-238-8000 or 877-986-8083 using the code “ESIP SUMMER MEETING BLOCK”.

Meeting Registration: 
Before the early registration deadline, registration is $415 for ESIP partner affiliates and $550 for non-partner affiliates. After June 28th, registration is $515 for partner affiliates and $650 for non-partner affiliates. The student registration rate is $150. A special one-day rate is available for $200. The teacher registration rate is $50. Teachers attending the Teacher Workshop will be refunded the registration fee after attending the meeting plus a stipend of $200. A full refund will be given for all registration types until June 19th.

REAL ID Act: The REAL ID Act establishes minimum security standards for license issuance and production and prohibits Federal agencies from accepting driver’s licenses and identification cards from states not meeting the Act’s minimum standards. If your state is non-compliant and does not have an extension, you may not be able to board a federally regulated commercial aircraft with just your state-issued driver’s license. Please visit https://www.dhs.gov/real-id prior to travel to find your state status and ensure you have appropriate identification.

Questions: Contact staff@esipfed.org

Machine Learning/Data Science Internship

Written by

Mixing technology, data, and first-in-class innovation, EagleView® is not only leading the property data analytics market, but also changing lives along the way. Come join us and make great things happen!

EagleView is a fast-growing technology company driving game changing innovation in multibillion-dollar markets such as property insurance, energy, construction, and government. Leveraging 17 years of the most advanced aerial imaging technology in the world, along with the most recent advances in machine learning and AI, EagleView is fundamentally transforming how our customers do business.

At EagleView, we believe that making our culture engaging and empowering are keys to success. Our kitchens are stocked 24/7; social, athletic, and wellness opportunities are plentiful; and the growth, education, and potential of employees is a top priority, making EagleView a “Best Place to Work” for more than five years running.

Job Description

We are looking for a talented student that’s interested in a Machine Learning, Data Science position. You’ll have the opportunity to work with a fun, hardworking and talented team to help develop and run neural net classifiers for aerial and drone imagery.

PRIMARY RESPONSIBILITIES

  • Help to aggregate, clean, and organize training data for machine learning
  • Help evaluate and document model performance
  • Work with other members of the Machine Learning Team to scale the use of neural networks for imagery classification and other applications
  • Research and experiment new technologies that can improve algorithm applications

Skills & Requirements

  • Experience with Python or similar language
  • Experience Amazon AWS or other cloud compute services
  • Working knowledge of Linux-based command line environments
  • Working toward a Bachelor’s Degree, preferably in science, data science, engineering, computer science, or related field

Apply Online