Programs Computational neurosciences: what to expect contentwise?

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The discussion centers on the excitement surrounding a new Master's program in computational neuroscience, which combines elements of signal processing, circuit modeling, machine learning, and biology. The program aims to address a growing need for engineers skilled in these interdisciplinary areas, as evidenced by similar offerings at other universities. The curriculum is divided into three main categories: technology, focusing on neuroprosthetics and motor function analysis; data science and machine learning, emphasizing statistical methods and signal processing; and imaging, which includes topics like tomography and computer vision. Participants are encouraged to share their experiences with computational neuroscience to assess the program's relevance and quality compared to traditional syllabi.
fatpotato
Hello,

I was going back to university for Grad school (Master's degree) this fall in Electrical Engineering, but since my application and admission, the uni created a brand new program in computational neurosciences, and I am heavily considering to follow this path instead. Thrilling!

However, I am not really familiar with the field. I have read the syllabus and have been memserized by course descriptions. From what I read, I imagine this field as the perfect mix of signal processing, circuit modelling and analysis, machine learning, stochastics and of course, biology.

Is this correct? Am I idealizing? I fear being too optimistic, and would love to hear about your experience if you have an academic background in comp. neuro. Please share!

Thank you
 
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Hello,

I can post the list of courses and program structure, which should be found in attachment. Otherwise, follow this link: Neuro-X Master at EPFL

This is a new program which aims to merge a lot of courses previously proposed as electives or as a minor. I suppose that there is a need for this type of engineers, for I have seen a few other universities offering this kind of studies these last few years.

Courses are distributed among three categories :
  1. Technology: most of the content here was included in the former "neuroprosthetics" minor. This category focuses on designing interfaces for the body and analysing motor functions of the nervous system.
  2. Data science and ML: most the content here was included in the former "computational neuroscience" minor, with a focus on machine learning, signal processing and statistics.
  3. Imaging: covering all subfields: from tomography and optics to image processing and computer vision.
Courses in the last category is organised a bit like a medical symposium, where "hot" topics and papers are discussed and analysed, and can lead to a publication from the students.

For people who studied computational neurosciences: how does this differ from the syllabus you followed? Does this syllabus look good to you?
 

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