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Jobs Posted on the Whova Community Board of ML-HELIO 2022

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Postdoctoral Research Associate
University of New Hampshire
This postdoc will apply big data and machine learning techniques to several decades of ground and space observations to improve our understanding and predictions of geomagnetically induced currents. The postdoctoral research is part of a 4-year, 4-million-dollar project conducted in partnership between the University of New Hampshire and the University of Alaska-Fairbanks (UAF). The postdoc will also have the opportunity to be involved in the space weather underground program (SWUG) that works with local high school students to build, deploy, and analyze ground magnetometers.

Candidates with experience in machine learning and/or ground magnetometer data analysis are particularly encouraged to apply.
Post-Doctoral Associate in Machine Learning for Space Weather
University of Colorado
The Cooperative Institute for Research in Environmental Sciences (CIRES) encourages applications for a full-time Post-Doctoral Associate to work on the development, validation, and calibration of space weather models, using machine learning and physics-based models. This position contributes to a NASA-funded project within the ‘Space Weather with Quantified Uncertainty’ program. The main objective will be to deliver probabilistic space weather forecasts with their associated uncertainties. In particular, this position will focus on the forecast of solar wind quantities (speed and magnetic field). The position will involve close collaboration with other post-docs, students, and senior members of the project, which are divided between CIRES, the Computer Science Department and the Space Weather Technology, Research, and Education Center (SWx-TREC) at CU Boulder, and the space physics group at the University of California, Los Angeles. The position will be primarily based at CU Boulder, although remote working can be considered.

Product and Community Lead for the 2i2c Project
"The 2i2c team is looking to hire a new team member! We are seeking a product and community lead with the following two goals:

Empower the communities we serve to have impact with our infrastructure.

Guide our development and service design to reflect the needs of our users.

This role will work alongside our engineering team as a partner, and will serve as a high-bandwidth interface to the communities that we work with."
Post-doctoral position, Research Associate in Machine Learning for Heliophysics
FHNW University of Applied Sciences North Western Switzerland
The FHNW Institute for Data Science is involved in various astroinformatics projects. It provides software components to ground segment data processing infrastructures (Euclid, Dark Energy Survey) or to science pipelines (Solar Orbiter, SKA). A core research area is the study and implementation of data driven methods to exploit the data collected in these missions, especially in the context of the Swiss National Science Foundation RODEM project (Robust Deep Density Models for
High-Energy Physics and Solar Physics,

Your tasks will include

* Design and application of deep learning models in different use cases involving principally solar data from spacecraft. An example is the use of generative models designed to provide efficient and highly discriminative classifiers for predicting solar flares.

* Participation to the global advancement of RODEM and possibly create links and synergies with associated further astroinformatics projects of the institute.

* Work closely with the RODEM team in house and in our partner institution, the University of Geneva. Support the in-house team in accomplishing the data management and data engineering tasks needed to facilitate the application of data-driven methods to large datasets.

* Possibly participation in our teaching activities

New solicitations are out for these NSF programs which highlight ML as a focus area. See the solicitations or talk to a NSF Program Officer for more info
Link: None
Postdoctoral researcher
Southwest Research Institute
2 year postdoctoral research on machine learning applied to heliophysics. The main project involves flare forecasting using historical observations. Tasks include historical data homogenization, training ensembles of neural networks, and quantification of uncertainty.

My goal is to create a sustainable position in which there will be time devoted to proposal writing in the goal of making the transition to a research scientist position, so grant writing is part of the job.

It is one of my main dreams to build a nurturing team where we use novel techniques for ideation and collaboration modeled after five years of experience leading challenges in the Frontier Development Laboratory. As such, you can expect a lot of interaction between team members: Pair coding, code reviews, standup meetings, git versioning, and mindful interaction. Kindness and the willingness to help each other is highly preferred.

It is common for under-represented minorities to self-select out of positions without clear measurable requirements. If you can understand, run, and develop frameworks similar to those presented in this book: you are ready to join our team.

I want to create a highly diverse team across many axes of diversity. Expertise with heliophysics problems is not a requirement, if there is expertise on machine learning in other domains.

The position is not formally opened yet, but if you are interested, please let me know.

Point of Contact: Andrés Muñoz-Jaramillo
Research Scientist - High Performance Computing
Amazon Web Services
Are you a hands-on High Performance Computing (HPC) expert who can make a huge impact on a dynamic, fast moving business? Do you want to help Customers develop and migrate mission-critical HPC workloads? Are you detail-oriented and creative? Do you like to collaborate with others to achieve goals? Then this is the position for you.

In this role, you will utilize your domain expertise to tackles the complexities of build, integration and innovation in the advanced computing space. While we don’t expect you to be an expert in all of these areas, a successful candidate will have demonstrated expertise in some combination of:

* Big data technologies like Hadoop, Hive, Oozie, Presto, Hue, Spark, etc.
* High Performance Computing components including Compute (CPU/GPU/FPGA), Storage, Networking and Resource Managers
* AWS services such as AWS Batch, AWS EMR, AWS ParallelCluster, AWS Braket
* High-performance storage solutions like FSx Lustre
* Scientific programming environments such as Julia, Python, Mathematica, MATLAB
Frontier Development Lab 2022 - Paid research opportunities for PhD students and postdocs
Frontier Development Lab
The Frontier Development Lab (FDL) is an applied artificial intelligence research program with the primary purpose of advancing the application of machine learning, data science and high performance computing to solve problems of material concern to humankind.
We take great care in recruiting an interdisciplinary team of science and field experts, PhDs and Postdocs to surround each challenge, and then supporting you through an 8 week accelerated research sprint, with huge resources, to deliver world class research that is a powerful platform for a research career in academia, federal government or big tech.
FDL results have been deployed on NASA and USGS programs, showcased on the front page of, and are regularly accepted to respected journals and scientific conferences in AI, Earth and space science domains.
This is an opportunity to join a brilliant team of interdisciplinary researchers. Researchers on the teams will be paid a fixed stipend for their efforts.
Research applications close on Sunday 3 April 2022. Interviews are taking place now, so we encourage you to apply as soon as possible.
Data Systems Software Engineer
Full description in link

The Laboratory for Atmospheric and Space Physics (LASP) is encouraging applications for people with software engineering and/or scientific programming skills. You will support scientific software engineering and science data center projects for space missions. Project scientific topics include Astrophysics, Space Physics, Planetary, Solar, Earth Atmospheric and Climate missions.

Our team values dedication, excellence, growth, and curiosity. We are looking for applicants that connect and communicate well with mixed teams of students, scientists, other software engineers, and external customers such as the science community and NASA personnel.

Applicants need to be able to learn quickly and balance competing priorities. On-the-job training is expected, and mentoring/support is a highly developed part of our team dynamic.
Machine Learning Engineer
Amazon Web Services
Excited by using massive amounts of data to develop Machine Learning (ML) and Deep Learning (DL) models? Want to help public sector, medical center, and non-profit customers derive business value through the adoption of Artificial Intelligence (AI)? Eager to learn from many different enterprise’s use cases of AWS ML and DL? Thrilled to be key part of Amazon, who has been investing in Machine Learning for decades, pioneering and shaping the world’s AI technology? At Amazon Web Services (AWS), we are helping large enterprises build ML and DL models on the AWS Cloud. We are applying predictive technology to large volumes of data and against a wide spectrum of problems. Our Professional Services organization works together with our AWS customers to address their business needs using AI. AWS Professional Services is a unique consulting team. We pride ourselves on being customer obsessed and highly focused on the AI enablement of our customers. If you have experience with AI, including building ML or DL models, we’d like to have you join our team. You will get to work with an innovative company, with great teammates, and have a lot of fun helping our customers. If you do not live in a market where we have an open Data Scientist position, please feel free to apply. Our Data Scientists can live in any location where we have a WWPS Professional Service office. We’re looking for top architects, system and software engineers capable of using ML and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.
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