- Joined
- 9/15/11
- Messages
- 2
- Points
- 11
Hi everyone, I'm a first time poster and virgin to the world of financial engineering. I'm in the middle of a Computational Neuroscience PhD and one of my advisers (a CS Machine Learning specialist) suggested I look into hedging my bets for after school jobs with quant-finance skills considering my current work is in statistical analysis of large multidimensional time-series data-sets. From what I understand, the field is pretty much looking for Physics or Engineering PhDs with few exceptions, so I was hoping to get some feedback on my skills, see if that proposal was realistic, and what I might do to develop a quant resume during the two years I have left.
So, here goes:
My degree will be from a top 50 US school that is renowned for Machine Learning and Data Mining,
PhD - Cognitive Neuroscience
MS - Statistics
MA - Cognitive Neuroscience
Coursework: 3.8+ or so gpa
Machine Learning, Probabalistic Learning, Stochastic Processes, ANNs, Computer Vision, Computational Modeling in Neuroscience, Computational Stats including plenty of optimization methods like MCMC, EM, GD methods and so on, plenty of probabilistic modeling, algorithm optimization, and a smattering of neuroscience and engineering stuff.
Programming:
C/C++/C#, MATLAB, R, SAS, Python, CUDA, MS Office stuff including Excel certainly but no Access experience, and will be proficient at Java by the end of the year.
ML/DM:
Placed in top 3 of a few open machine learning and computer vision challenges.
Research:
I work on statistical EEG processing and algorithm development for EEG Brain-Computer Interfaces. So, most days I'm applying machine learning, statistical modeling and data mining methods to large time-series data-sets, building filters and writing software. My thesis will be along these lines. I work with a few other ML and engineering fields from time to time like computer vision and cognitive robotics.
Financial Background:
(null)
I can beg, borrow or steal my way into some courses in the time I have left. I'd love some suggestions of what I may want to do, or what I may suite me.
Well, I guess that's it. I'd appreciate any chides or advice.
Thanks in advance,
- K
So, here goes:
My degree will be from a top 50 US school that is renowned for Machine Learning and Data Mining,
PhD - Cognitive Neuroscience
MS - Statistics
MA - Cognitive Neuroscience
Coursework: 3.8+ or so gpa
Machine Learning, Probabalistic Learning, Stochastic Processes, ANNs, Computer Vision, Computational Modeling in Neuroscience, Computational Stats including plenty of optimization methods like MCMC, EM, GD methods and so on, plenty of probabilistic modeling, algorithm optimization, and a smattering of neuroscience and engineering stuff.
Programming:
C/C++/C#, MATLAB, R, SAS, Python, CUDA, MS Office stuff including Excel certainly but no Access experience, and will be proficient at Java by the end of the year.
ML/DM:
Placed in top 3 of a few open machine learning and computer vision challenges.
Research:
I work on statistical EEG processing and algorithm development for EEG Brain-Computer Interfaces. So, most days I'm applying machine learning, statistical modeling and data mining methods to large time-series data-sets, building filters and writing software. My thesis will be along these lines. I work with a few other ML and engineering fields from time to time like computer vision and cognitive robotics.
Financial Background:
(null)
I can beg, borrow or steal my way into some courses in the time I have left. I'd love some suggestions of what I may want to do, or what I may suite me.
Well, I guess that's it. I'd appreciate any chides or advice.
Thanks in advance,
- K
