FAQs: On the Edge Fellowship

Read on for our FAQs on the new WILDLABS Fellowship: On the Edge, including information on applying to this opportunity. 

Looking for the fellowship's terms and conditions? Find them here 

Header Image: Arribada / ZSL

Date published: 2021/07/20

Our team will also take questions in this discussion thread in the WILDLABS Community, so please jump in there and post your questions if you need further information. We will keep these FAQs updated with summarised information as we receive questions about this Fellowship opportunity.

What are the expected deliverables or outcomes for Fellows?

The chosen Fellow(s) will deliver and be featured in:

  • Quarterly updates on the progress of the supported project, either through blogging, video updates, papers, livestreams, or other media (These updates will be shared through Edge Impulse’s and WILDLABS’ various content channels)
  • Two interviews with WILDLABS to begin and end the Fellowship
  • At least one appearance at a WILDLABS virtual event to highlight your project
  • A concluding case study at the end of the year, summarizing the project’s development, successes, next steps, etc.
  • Ongoing yearly updates on project’s continuation (if applicable) 

All communications such as project updates, interviews, case studies, etc. will have the editorial support of the WILDLABS team, and the WILDLABS team will work closely with Fellows to keep them informed of upcoming publication deadlines and expectations. 

What is the duration of the Fellowship?

Fellowships selected in this application period will last one year from the start date in October 2021.

  • When will the chosen Fellow(s) start? The chosen fellows will be notified on or around September 22nd, 2021, and the duration of the fellowship will begin upon receiving the award of $6,500 in October 2021. 
  • What if my project must begin by a certain date due to field seasons, lab availability, university requirements, etc.? If your project is dependent on a specific timeframe, please indicate this within your application and we will take your needs into account.
  • Is it possible for the Fellowship to be extended based on the Fellow’s progress within the course of the year? The expectation for chosen fellows from this period is for one year only. Any future extension is dependent on funding, availability of staff, the project’s scope, and many other internal factors, and is up to the discretion of WILDLABS and Edge Impulse’s Fellowship committee. 

What types of projects are you looking for?

No matter the species, environment, or conservation challenge your project is based around, if you’ve got a machine learning-powered idea in development, your project can be considered for this Fellowship.

Where possible, we would also love to see the selected projects support the wider conservation tech community, either through the development of open source tools or data, replicable processes, case studies, or other resources that will benefit your peers.

In the spirit of supporting projects that can create immediate impact, our Fellowship is designed for applicants whose projects have been tested in some capacity or have been proven viable beyond the concept stage. This may include testing in field or lab, personal trials, through modeling, or through past experience. 

While we welcome Fellows to further explore the possibilities throughout the Fellowship and put their new machine learning skill sets to good use, this Fellowship is not intended for purely exploratory projects - the end result should be something tangible, scalable, replicable, or ready for the next stage of development or deployment.

While machine learning is an integral part of this Fellowship and should factor heavily into your goals, applicants by no means need to be experts in AI - Edge Impulse’s team will help you acquire the needed machine learning skills through mentorship. However, applicants should have a solid understanding of how they will use machine learning, and what the possibilities are for incorporating machine learning tools into their project’s current and future development. 

What does "ML on the edge" mean?

ML on the edge refers to embedded machine learning, of which Edge Impulse is the leading development platform. Edge Impulse enables development experience for machine learning on embedded devices for sensors, audio, and computer vision, at scale. Embedded machine learning solutions dramatically speed up development time, making solutions that would have taken years to develop a reality within weeks. Read more about embedded machine learning solutions on Edge Impulse, and check out our beginner's tutorial with Edge Impulse's Dan Situnayake.

What are the judging criteria for projects?

Projects will be assessed based on how well they meet the following criteria:

  • The proposed project for the Fellowship year leverages machine learning on an edge device to address a specific conservation challenge identified by the Participant. All projects should significantly feature machine learning aspects, and be able to demonstrate how machine learning will enhance or transform their final results.
  • The proposed machine learning application has the potential for further development or to be scaled up to be made available for use by other conservationists with similar use cases.
  • Submitted projects should have some previously demonstrated viability in the field, lab, personal trials, through modeling, or through past experience. Projects that could realistically reach field testing, deployment, or use by the end of one year are ideal; however, we also encourage projects that can make significant progress toward development or scalability to apply.
  • The Fellow demonstrates commitment and enthusiasm for engaging with a mentor and the broader conservation tech community, and understands how these can be leveraged to support their work
  • The Fellow demonstrates commitment to documenting their work and processes effectively so that others can learn from their efforts and can input to support problem solving 
  • Applicants of all skill levels, stages of development, and professional or academic affiliations (including independent conservation tech developers) are welcome to apply.
  • Women and underrepresented groups are highly encouraged to apply, as building accessibility to machine learning tools and conservation technology networks is a key aspect of this fellowship.

Read more about judging criteria and the selection process in our Terms and Conditions.

I have questions about the application process or materials, and need help to submit everything. Who do I contact?

Email [email protected] for assistance. To ensure you have time to receive assistance if needed and complete your application before the deadline, we recommend trying to submit your application as soon as possible.

Who will review the applications and make the final decision?

Applications will be reviewed and chosen by a selection committee comprised of WILDLABS and Edge Impulse leaders. 

Is the information contained in my submitted application going to remain confidential?

Yes, applications will remain confidential in adherence with WILDLABS’ privacy policy and the fellowship Terms & Conditions. We will not publicly share information provided in any applications without express permission received from the applicant in advance.

Applications will be retained by the WILDLABS team for records, and applicants may be contacted outside of the fellowship program about their work in the future.

By agreeing to become a Fellow in this programme, Fellows consent to WILDLABS and Edge Impulse sharing personal data (in case this is provided in the application) with third parties only insofar as this is required for the proper execution of the chosen Fellow’s project.