We are seeking enthusiastic applicants for a Post-Doctoral Fellowship position to help with the collection and analysis of large brain-imaging datasets. The successful candidate will use state-of-the-art artificial intelligence methods, with the aim of better understanding psychiatric disorders in young people with mental illness, particularly anxiety and depression. Our goal is to understand better the causes and mechanisms of certain psychiatric disorders, improve their definition and classification, and ensure the best treatment can be offered to psychiatric patients.
The successful candidate will develop and apply deep learning algorithms to multi-modal imaging datasets that include MRI (functional, structural), EEG, MEG, and associated behavioral and clinical data. The methods developed by the successful candidate will be used to:
- Integrate these diverse sources of information.
- Inform the construction computational models in psychiatry.
- Test the validity of such models.
Candidates with a strong computational background (e.g. PhD in Engineering, Physics, Computer Science, Mathematics, Statistics, Computational Neuroscience, and related areas) who are interested in brain development and psychopathology, are particularly encouraged to apply. Requirements for this position include:
- Strong machine learning experience;
- Programming experience in Python (preferably), or in R/Matlab/Octave;
- Experience with open source machine learning libraries such as Scikit-learn, Theano, and/or Tensorflow;
- Excellent interpersonal and written (English) communication skills.
Background experience in psychiatry or knowledge of neuroimaging software are not required. However, the candidate will be expected to learn some of these topics as part of their role in our research group.
The successful candidate will work jointly with the laboratories of Drs Pine and Stringaris, and together with Dr Anderson Winkler, Staff Scientist. Please write to Drs Pine (firstname.lastname@example.org), Stringaris (email@example.com) or Winkler (firstname.lastname@example.org) with your application and CV.