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| - | <span style="color:navy">Frontiers in Earth surface dynamics: creating a research proposal.</span>
| + | Après une rapide introduction générale sur Python, le cours |
| - | | + | se concentre principalement sur les applications scientifiques de |
| - | The aim of this course is to provide some training in the presentation of new ideas and the creation of research proposals. As a subject I chose Earth surface processes, yet the topic is not as important as the objective, which is to practice presenting research ideas to your peers. The intention of this course is to give an introduction to how a grant proposal is created. In the current academic career structure the selling of ideas is a key skill in achieving research grants from the ANR, ERC and EU, and a getting a job. The secondary objective is to introduce the study of Earth surface processes.
| + | Python, notamment basées sur les librairies scientifiques NumPy, |
| - | | + | SciPy et Matplotlib. |
| - | This three day course will run over two sessions: two days of talk and discussion followed by a day of presentations, with a week in between. The first part will be a over two days where I introduce some of the current research into landscape evolution and how it is applied to understanding past climate on the Earth and Mars. I will also explore how we currently think mantle dynamics interacts with the Earth's surface and how change in sediment accumulation might reflect past surface uplift. I will try to show where current research ends and give an idea to some of the open questions.
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| - | Students will then form groups (across disciplines if possible) and pick a question/make a question of their own. The challenge will then be for the groups to create a research proposal summary (one page of text) and present this idea in the following week. Presentations will follow the rules of the CNRS concours: I will allow 15 minutes talk and 15 minutes questions from those not presenting.
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Version du 1 février 2016 à 14:20
Après une rapide introduction générale sur Python, le cours
se concentre principalement sur les applications scientifiques de
Python, notamment basées sur les librairies scientifiques NumPy,
SciPy et Matplotlib.
