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Postdoctoral Fellow/Center for Biomedical Information - 16000000OC : Knoxville, TN, United States

A postdoctoral position is available in predictive modeling at UTHSC-ORNLCenter for Biomedical Informatics. The successful candidate will work with Dr. Oguz Akbilgic on the development and implications of statistical methodology and machine learning algorithms focusing on problems from biomedical informatics. These researches are intended to lead to both publications in high-quality peer reviewed journals as well as successful grant submissions. The initial appointment will be for 12 months. Depending on the performance and funding availabilities, an extension may be considered for up to six more months.

Qualifications

UTHSC-Pediatrics
Position Title: Postdoctoral Fellowship
Position Description: A postdoctoral position is available in predictive modeling at UTHSC-ORNL Center for Biomedical Informatics. The successful candidate will work with Dr. Oguz Akbilgic on the development and implications of statistical methodology and machine learning algorithms focusing on problems from biomedical informatics. These researches are intended to lead to both publications in high-quality peer reviewed journals as well as successful grant submissions. The initial appointment will be for 12 months. Depending on the performance and funding availabilities, an extension may be considered for up to six more months.

Position Qualifications: Applicants should (or expecting to) have a PhD in statistics, applied mathematics, data sciences, or a related field with a graduation date not earlier than 1/1/2014. The applicants should have a strong background on statistics and machine learning. Knowledge and experience in statistical computing is needed. Applicants should evaluate their qualifications by filling the check-list below. Applicants scoring exactly 5/5 on section A, and at least 10/16 in total are encouraged to apply.

A. Necessary Qualifications:

Published (or in press) a part of your phd work in a peer-reviewed journal covered by SCI, SCI-Expended, or PubMed.

Scientific programming and statistical computing via Matlab and R

SQL, database management

Training and/or knowledge on regression, classification, clustering, artificial neural networks, support vector machines

Statistical analysis via SPSS or SAS or equivalent.
B. Preferred Qualifications

Formal training or experience in biomedical informatics

Scientific Programming with C/C++

Scientific Programming with Python

Programming with SAS

SPSS Modeler

Training and/or experience in Information Complexity based Model Selection

Training and/or experience in pattern recognition

Training and/or experience in signal processing

Training and/or experience in text mining

Training and/or experience in image recognition

Training and/or experience in parallel computing

Application Information: Applicants should email a copy of their CV including contact information of three references, the check-list above, and a cover letter to Dr. Oguz Akbilgic with subject “CBMIPD + last name + your score on check-list”.

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