Description

Each year, the BLUECONNECT project will provide 8-12 graduate and postgraduate students from South Africa and Norway with a unique opportunity to interact with high-profile scientists as part of a transdisciplinary and advanced training program. This competence building will enhance science-based ocean research in the future, with strong focus on kelp forest ecology. The course will use a multi-faceted approach that includes lectures, case studies and practical field experience. In this way, participants will obtain a hands-on and integrative experience that covers a wide range of topics. Under the supervision of expert researchers in this field, practical activities will be conducted as part of an actual kelp research program. The students will participate in the field work, gaining firsthand experience in sampling and experimental design and methods. The course will also foster the development of transversal skills such as networking and international scientific collaboration, as well as science communication, and outreach.

 

The course syllabus will include

• Scientific research techniques (practical field work covering 200 km coastline in South Africa)

• Advanced statistics and analysis of biological data

• Use of remotely sensed data

• Fundamental principles and recent advances in Marine Ecology, Theory, Experimental Design and Kelp Forest Ecology (classroom lectures)

• Science communication, writing skills and career opportunities.

 

Students will be assigned relative readings and assignments (in R) to complete before the course begins (8 to 12 h).

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Application

Interested students should submit the following to kfilbeedexter@gmail.com.

Format: single pdf document

Subject line: BlueConnect Course 2020_last name of applicant

1.  Statement of Interest detailing the relevance of this course to your ongoing research,

any prior experience (academic or other) and career aspirations (300 words)

2. Graduate thesis topic, description and timeline (200 words)

3. Transcript (undergraduate and/or graduate)

4. Letter of support from thesis supervisor (max 1 page)

Deadline = Jan 31, 2020