Postdoctoral research fellow in biological data mining and modeling – Bioinformatics Institute, A*STAR, Singapore

Job Description:

ISCB Job Board

Postdoctoral research fellow in biological data mining and modelingBioinformatics Institute, A*STARSingapore A postdoctoral research fellow position in the areas of biological data mining and modeling is available in the Loo lab (http://web.bii.a-star.edu.sg/~loolh) at the Bioinformatics Institute (BII), Singapore. The group focuses on studying complex cellular responses to chemical and biological compounds using quantitative data modeling and cellular imaging methods. The successful candidate will develop new data mining and modeling algorithms and tools for predicting drug toxicity based on chemical structures, cellular images, and gene expression profiles. The candidate will have the opportunity to work in a highly interdisciplinary and stimulating environment. Candidates must have a strong quantitative background, with a Ph.D. in computer science, computational biology, bioengineering, chemical engineering, electrical or computer engineering, or other related fields. Strong knowledge in machine learning, data mining, regression analysis, statistics, and programming (R and/or Python) are required. Candidates with interdisciplinary training in chemistry/biology and computing are especially encouraged to apply. Candidates must also possess good communication skills, and be fluent in both spoken and written English.

Job Information Position Type: Postdoctoral Researcher
Start Date: ASAP
Duration: Full Time
Status: open Contact Information
Bioinformatics Institute, A*STAR
Lit-Hsin Loo
loolh@bii.a-star.edu.sghttp://web.bii.a-star.edu.sg/~loolh

How To Apply:Applicants should send
* a one-page cover letter briefly describing prior research experience and accomplishments,
* a one-page statement of research interests,
* CV,
* contact information of two references, and
* reprints of one to two publications
to Dr. Lit-Hsin Loo (loolh@bii.a-star.edu.sg).

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Skills :

• Bioinformatics
• Biology
• Computational Biology
• Machine Learning
• Modeling
• Statistics

Areas :

• Bioinformatics
• Computational Biology

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Additional Info:

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