Application form - ML Training

Application form: ML Training

Applicant information

1. Name

2. Date of birth

3. Gender

4. Country

5. Address

6. Contact number

7. Organisation/Institution name

8. Designation

9. Email address

10. Contact name and number, in case of emergency

Education and technical background

11. Highest degree earned

Bachelor

Master

PhD

Other

12. Field of expertise

13. How is your work or study related to cryosphere and related hazards in mountain environment?

14. How will this training benefit your current or future work?

Additional information

15. Do you have a laptop that can run computationally intensive models?

Yes

16. Have you previously attended any ICIMOD or similar regional training?

Yes

16.1 Please specify the year and training name

17. Are you comfortable with being photographed, recorded, or approached for quotes during the training for documentation, outreach, or promotional purposes (e.g., social media posts, reports, or publications)?

Yes

18. Would you be interested to be added in the cryosphere mailing list?

Yes

19. Please specify any special dietary requirements and additional physical needs we should be aware of.

Technical Task

20. Please carry out the following tasks and upload your Resume (max 1 page), both tasks, including the maps, scripts, and their respective descriptions as a single document either in .docx or .pdf format. Please ensure that the work is completed independently and not generated using AI tools:

Task 1: Generate false color composite map
Select Rikha Samba glacier (28.823742°,83.490774°) and prepare a false color composite (FCC) map using satellite imagery, such as Landsat or Sentinel. Write a description max of 250 words that explains the map in detail. The description should highlight the features visible in the FCC, focusing on the glacier’s extent, ice and snow distribution, and the surrounding landscape. Also discuss how the FCC helps in identifying glacial characteristics and why this type of imagery is useful for glacier monitoring.

Task 2: Time-series temperature analysis
Prepare a time-series analysis of temperature for the same glacier location using ERA5-Land data. The analysis should cover the time period beginning from your date of birth and ending on 30 September 2025. Present the results as a time-series graph, showing how temperature has changed over this period. Write a description max of 250 words discussing the observed temperature trends, variability, and potential implications for glacier.

The file size should not exceed the specified limit of 10 MB.

Choose File