| Feb. 13, 2024, 4:20 p.m. |
Created
43
|
[{"model": "core.projectfund", "pk": 67880, "fields": {"project": 16138, "organisation": 5, "amount": 0, "start_date": "2018-10-01", "end_date": "2023-05-31", "raw_data": 188036}}]
|
|
| Jan. 30, 2024, 4:25 p.m. |
Created
43
|
[{"model": "core.projectfund", "pk": 60701, "fields": {"project": 16138, "organisation": 5, "amount": 0, "start_date": "2018-10-01", "end_date": "2023-05-31", "raw_data": 168920}}]
|
|
| Jan. 2, 2024, 4:16 p.m. |
Created
43
|
[{"model": "core.projectfund", "pk": 53560, "fields": {"project": 16138, "organisation": 5, "amount": 0, "start_date": "2018-10-01", "end_date": "2023-05-31", "raw_data": 142636}}]
|
|
| Dec. 5, 2023, 4:25 p.m. |
Created
43
|
[{"model": "core.projectfund", "pk": 46303, "fields": {"project": 16138, "organisation": 5, "amount": 0, "start_date": "2018-09-30", "end_date": "2023-05-30", "raw_data": 123743}}]
|
|
| Nov. 27, 2023, 2:16 p.m. |
Added
35
|
{"external_links": []}
|
|
| Nov. 21, 2023, 4:44 p.m. |
Created
43
|
[{"model": "core.projectfund", "pk": 39044, "fields": {"project": 16138, "organisation": 5, "amount": 0, "start_date": "2018-09-30", "end_date": "2023-05-30", "raw_data": 82667}}]
|
|
| Nov. 21, 2023, 4:44 p.m. |
Created
41
|
[{"model": "core.projectorganisation", "pk": 118452, "fields": {"project": 16138, "organisation": 11077, "role": "LEAD_ORG"}}]
|
|
| Nov. 21, 2023, 4:44 p.m. |
Created
40
|
[{"model": "core.projectperson", "pk": 74560, "fields": {"project": 16138, "person": 22113, "role": "SUPER_PER"}}]
|
|
| Nov. 21, 2023, 4:44 p.m. |
Created
40
|
[{"model": "core.projectperson", "pk": 74559, "fields": {"project": 16138, "person": 22114, "role": "SUPER_PER"}}]
|
|
| Nov. 20, 2023, 2:06 p.m. |
Updated
35
|
{"title": ["", "AI for megacities: Understanding the impact of climate extremes"], "description": ["", "\nRegional and local scale extreme events (such as heat waves) will become more frequent over the next few decades, with rising mean temperature and increased climate variability. While climate models capture broad scale spatial changes in climate phenomena, they struggle to represent extreme events on local scales. Such events are crucial to providing actionable and robust climate information to forecast, among other things, energy demand. The student will apply Bayesian statistics and machine learning in new and innovative ways to help transform the field of environmental data science.\n\n"], "extra_text": ["", "\n\n\n\n"], "status": ["", "Closed"]}
|
|
| Nov. 20, 2023, 2:06 p.m. |
Added
35
|
{"external_links": [62987]}
|
|
| Nov. 20, 2023, 2:06 p.m. |
Created
35
|
[{"model": "core.project", "pk": 16138, "fields": {"owner": null, "is_locked": false, "coped_id": "18fb4667-eb29-4bc5-888d-e2a95b70a051", "title": "", "description": "", "extra_text": "", "status": "", "start": null, "end": null, "raw_data": 82650, "created": "2023-11-20T14:01:09.426Z", "modified": "2023-11-20T14:01:09.426Z", "external_links": []}}]
|
|