My research group is hiring a Scientific Software Engineer to help develop software that facilitates science, contribute to research in data-intensive ecology, and improve scientific research and computing through training and modeling competitions.
We are actively involved in data-intensive computational research, open source software development, and open approaches to science. The engineer will work as part of a collaborative group, including undergraduates, graduate students and postdocs, using large amounts of ecological and environmental data to understand natural systems. They will develop and maintain open source software designed for working with large amounts of heterogeneous data, collaborate on research projects making predictions for ecological systems, and help develop web infrastructure for scientists to share, evaluate and improve predictions. In doing so they will actively interact with, and contribute to, related efforts from other initiatives and projects in these areas (e.g., rOpenSci, Dat, Software Carpentry, Data Carpentry, DataONE, NCEAS).
Are you a software developer who’s interested in science? Great! Are you a scientist with strong software skills? Awesome! If you have some experience with Python or R, Git, database management systems, web development, spatial data, and/or PostgreSQL/PostGIS, we’d be excited, but what we’re really interested in is someone who is good with computers, interested in science, enjoys working on a variety of projects, likes learning new tools as needed, and works well in a diverse team.
The University of Florida is a great place to work in the computational, data-intensive, and informatics side of science. They have a major hiring initiative in “big data”, a new Informatics Institute that we are a part of, and a top notch Research Computing Center (aka HPC). In addition, I am a Moore Foundation Investigator in Data-Driven Discovery and actively engaged in the computational and data-intensive science communities. This makes my lab a good place to work if you enjoy that sort of thing (checkout our GitHub organization if you want to see what we’ve been up to recently). We also work hard to provide a positive and supportive environment that treats all members of the group as important contributors and actively values diversity.
This position has guaranteed support for the next five years. My goal is for this to be a long-term position in our research group and a model for similar positions in other research groups.
If you’ve made it this far you might be interested in a few more details of the projects this position might be involved in. These include:
- Developing, maintaining, and providing support for open source software for acquiring, cleaning, combining, and managing large numbers of heterogeneous datasets. This will include Python based development and maintenance of the EcoData Retriever software and the development of new software to automatically combine multiple datasets together for analysis.
Working in collaborative teams to conduct scientific research including the use of machine learning for making predictions and forecasts for ecological systems.
Developing, maintaining, and providing support for an open source system for publicly sharing ecological predictions and forecasts and automatically evaluating those predictions as new data is released. This system will be designed to allow researchers to collaborate and compete to improve predictions by uploading predictions to be compared to test data and/or by uploading code to make predictions.
Engaging with the broader community of projects involved in acquiring, cleaning, and combining heterogeneous datasets (e.g., rOpenSci, DataONE, dat), as well as those training scientists in the use of data and computation (e.g., Software Carpentry, Data Carpentry). This includes contributing to open source and participating in related conferences and hackathons.
To apply please visit the official University of Florida job ad. If you have any questions feel free to leave a comment on this post, drop me an email, chat with me on Twitter, or check this blog later in the week to find out why I think this will be a pretty rewarding job. You can also check out our websites to find out more about my lab and our interdisciplinary research group.
UPDATE: Here’s the post I promised on why this will hopefully be a rewarding job.