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조급한 마음에 하다보면 탈이 납니다.
22
- 님은 그래서 학벌 어디고 직장은 어디신지요?
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- 학벌 관련 주제는 정답이 없다고 봅니다.
김박사넷에선 학벌 왜 자꾸 거론하냐 의미없다는 식의 이야기가 나오는데,
그럼 도데체 서카포 나온 분들은 왜 뼈저리게 공부해서 간거임?
전 부산대 출신인데, 전 그 분들이랑 다르다고 봅니다.
제가 학벌이 낮으니까 연구적인 역량의 그릇은 그 분들이 크다고 봅니다.
학벌은 높을수록 좋습니다.
차이가 없다는 건 말도 안되는 겁니다.
차이가 없다고 괜찮다고 하는 분들?
그럼 자녀분들 대학 대충 보내시면 될 듯 싶네요.
근데 이건 또 싫죠? 흔히 말하는 지잡대가면 재수시키든 뭐든 하실 분들이...ㅎ
다만, 연구라는 심오한 행위는 정확히 어떻다고 단정지을 수는 없지만...
그릇이 넓은거랑 그릇의 모양은 다르다고 봅니다.
연구는 창작의 영역이기에 아무리 많이 알아도 그걸 구현화하는 건 별개의 이야기라고 봅니다.
이게 학벌 낮은 분들이 극복할 수 있는 부분이라고 봄.
수능하나로 평생 울여먹을건 아니지만,
모든 상황에서 비슷한 실적을 경쟁자와 내었을 때 학벌이 떨어지면 지는게 순리입니다.
학벌이 떨어지는 만큼 실적을 내야 승리를 쟁취할 수 있다고 생각합니다.
인정할건 좀 인정합시다.
21
- 유학가세요. 특히 사카포 이하 학부는. 괜히 돌아가지 말고. 그리고 가능한 한국에 돌아오지 말고.
25년전에 박사받은 나는 ㅆㅂ 군대 땜에 국내에서 인생 망쳐서 서울 구저그런데서 교수하면서 인생ㅜ낭비함. 이제라도 사업이라고 해보려고 힘쓰고 있으나 몸이 예전같지 않네
17
- 여기가 감정 쓰레기통이 아닌데...
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성균관대 IBS뇌이미징연구단 글로벌바이오메디컬학과 자연지능연구실 대학원생/박사후연구원 모집
2023.03.30
0
1560
Natural Intelligence Laboratory has open positions for postdoctoral researchers and graduate students. Led by Hansem Sohn (https://hansem.github.io/), the lab investigates how biological neural networks perform computation and generate intelligent behaviors. Specifically, we have two research projects :
1. Neural population dynamics of relational inference
How does the brain make inferences based on relations between objects? To tackle this question, we have collected electrophysiology data from the posterior parietal cortex while animals performed a visual search task based on object relations. The prospective postdoc/student is expected to analyze the data to study how the cortical population dynamics unfold during the relational inference. The data was collected using high-density linear probes (up to two Neuropixels) and will also provide a unique opportunity to study the role of cortical laminar structures. Ideal candidates will have a strong background in analysis of electrophysiology data, advanced statistical methods, and neural network modeling but opportunities to learn these will be provided. This will be a collaboration with Dr. Mehrdad Jazayeri at MIT.
2. Cortical processing of domain-general numerical information
In this project, we will tackle the following questions.
How does the brain represent ecologically relevant numerical information (e.g., number of apples) and perform computations based on those representations in a compositional manner?
Is there a neural circuit dedicated to numerical information processing, and is it common across different modalities of quantities such as number, time, and space?
What is the role of the prefrontal and posterior parietal cortex in processing numerical information? Are they rather independent modules or parts of a big recurrent network?
Do humans and non-human primates share similar neural mechanisms for magnitude processing?
We will use multiple approaches including careful design of behavioral tasks, computational modeling with Bayesian theory and artificial neural networks, large-scale electrophysiology, and state-of-the-art fMRI for both humans and non-human primates. Ideal candidates have extensive experience in more than one of the approaches but the lab will provide opportunities to learn new techniques.
Research topics are not limited to the above-mentioned projects and open to new proposals. Competitive salary or stipend (together with the tuition for graduate students) will be provided.
The lab is supported by Institute for Basic Science (IBS), Center for Neuroscience Imaging Research (CNIR), which houses multi-species animal facilities, multiple MRI scanners (3T, 7T), and cutting-edge neurophysiology systems. We offer a highly open, interactive, and collaborative research environment to promote innovative science. Sungkyunkwan university is a top-tier higher education in South Korea, located near its vibrant capital, Seoul (30 minutes drive).
If you are interested in working in the lab, please send a cover letter (stating why you are interested) and your CV/resume to Hansem Sohn, [my first name].[my last name] [at] gmail.com with your CV. The lab is committed to promote diversity and an inclusive environment. We value passion, strong work ethic (get things done!), scientific rigor and integrity, creativity (think outside the box!), and independence.
1. Neural population dynamics of relational inference
How does the brain make inferences based on relations between objects? To tackle this question, we have collected electrophysiology data from the posterior parietal cortex while animals performed a visual search task based on object relations. The prospective postdoc/student is expected to analyze the data to study how the cortical population dynamics unfold during the relational inference. The data was collected using high-density linear probes (up to two Neuropixels) and will also provide a unique opportunity to study the role of cortical laminar structures. Ideal candidates will have a strong background in analysis of electrophysiology data, advanced statistical methods, and neural network modeling but opportunities to learn these will be provided. This will be a collaboration with Dr. Mehrdad Jazayeri at MIT.
2. Cortical processing of domain-general numerical information
In this project, we will tackle the following questions.
How does the brain represent ecologically relevant numerical information (e.g., number of apples) and perform computations based on those representations in a compositional manner?
Is there a neural circuit dedicated to numerical information processing, and is it common across different modalities of quantities such as number, time, and space?
What is the role of the prefrontal and posterior parietal cortex in processing numerical information? Are they rather independent modules or parts of a big recurrent network?
Do humans and non-human primates share similar neural mechanisms for magnitude processing?
We will use multiple approaches including careful design of behavioral tasks, computational modeling with Bayesian theory and artificial neural networks, large-scale electrophysiology, and state-of-the-art fMRI for both humans and non-human primates. Ideal candidates have extensive experience in more than one of the approaches but the lab will provide opportunities to learn new techniques.
Research topics are not limited to the above-mentioned projects and open to new proposals. Competitive salary or stipend (together with the tuition for graduate students) will be provided.
The lab is supported by Institute for Basic Science (IBS), Center for Neuroscience Imaging Research (CNIR), which houses multi-species animal facilities, multiple MRI scanners (3T, 7T), and cutting-edge neurophysiology systems. We offer a highly open, interactive, and collaborative research environment to promote innovative science. Sungkyunkwan university is a top-tier higher education in South Korea, located near its vibrant capital, Seoul (30 minutes drive).
If you are interested in working in the lab, please send a cover letter (stating why you are interested) and your CV/resume to Hansem Sohn, [my first name].[my last name] [at] gmail.com with your CV. The lab is committed to promote diversity and an inclusive environment. We value passion, strong work ethic (get things done!), scientific rigor and integrity, creativity (think outside the box!), and independence.
https://natural-intelligence-lab.github.io/join/
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