The Research Foundation for Mental Hygiene, Inc.
Contact: Seonjoo Lee
Contact Email: see https://nyspi.applicantpro.com/jobs/
Description: The successful candidate will join the dynamic and interdisciplinary research group of Drs. Xi Zhu, Seonjoo Lee, and Franklin Schneier, focusing on collecting and analyzing imaging data, developing novel methods for analysis and integration of multimodal neuroimaging, behavioral and clinical data, and using machine learning artificial intelligence approaches to construct predictive network models in psychiatric disorders. Duties and Responsibilities include: Neuroimaging data collection and management Data analysis, and model building. Develop advanced deep learning and machine learning algorithms. Assist with organizing large scale multimodal neuroimaging dataset, brain imaging quality control and processing. Assist with grant applications, manuscript preparation and supervision of RAs and volunteers
Minimum Qualifications: Doctoral degree in biomedical engineering, electrical engineering, computer science, biostatistics, or a related field. At least 1 year of experience in data science and quantitative research. At least 1 year of experience in programming languages including Python or R. At least 1 year of experience in machine learning or deep learning models
Preferred Qualifications: Experience in working with an MRI scanner. Experience in developing state-of-the-art Machine Learning algorithms. Experience with one or more deep learning libraries such as PyTorch, TensorFlow, or Keras. Hands-on experience with neuroimaging processing pipelines. Excellent writing and communication skills. Strong interest in neuroscience and psychiatric research
Organization Information: New York State Psychiatric Institute and Columbia University Irving Medical Center
Instructions for Applying: Submit an application through our website at https://nyspi.applicantpro.com/jobs/ no later than June 11th, 2023. Please note- only applications submitted through our website will be considered.
Deadline: June 11th, 2023
Postdoctoral Research Associate in Bayesian Statistics
Department of Statistics, Texas A&M University.
Contact: Dr. Raj Guhaniyogi
Contact Email: firstname.lastname@example.org
Description: Dr. Rajarshi Guhaniyogi (Texas A&M) and Dr. Aaron Wolfe Scheffler (UC San Francisco) are seeking a postdoctoral research associate position at the Department of Statistics at Texas A&M University (starting as early as May 2024) for a National Institutes of Health (NIH)-funded research program. The research is related to one or more of the following areas: 1. Bayesian learning with heterogeneous objects (e.g., tensor, functional data); 2. Bayesian interpretable deep learning with heterogeneous objects; 3. Distributed Bayesian computation and Federated Learning with Gaussian processes and their variants; 4. Data sketching with random sketching matrices for efficient Bayesian inference with massive structured data. The details of some of the recent work in aforementioned directions can be found on the websites of the PIs (https://sites.google.com/view/rajguhaniyogi/home?authuser=0 and https://aaron-scheffler.github.io/). The postdoctoral scholar will have the opportunity if desired to directly work with leading neuroscientists at UC San Francisco Memory and Aging Center, who are also part of the NIH program, including world renowned experts on Alzheimer's disease. The position is crafted as a career-building opportunity for a junior scholar, emphasizing the development of a research program. The postdoc will be trained in conducting and presenting research, building regular collaboration with the leading biostatisticians and neuroscientists, publishing papers in methodology (and applications as desired), and creating software for wide dissemination of the research. The postdoc will be offered the mentored opportunity to write future NIH proposals with the PIs and their collaborators.
Minimum Qualifications: Doctorate in Statistics, Biostatistics, Computer Science, or related field required (at time of appointment). Expertise and interest in at least one of the research areas listed above.
Organization Information: https://stat.tamu.edu/
Salary Information: Highly competitive
Instructions for Applying: To apply, please email the following to Dr. Raj Guhaniyogi (email@example.com) and Dr. Aaron Scheffler (Aaron.Scheffler@ucsf.edu) with the subject line 'Bayes Stat Postdoc': 1. Most recent CV; 2. A writing sample (e.g., a published or an arxiv paper); 3. Contact information for 2-3 references.