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Apply Time
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🔹در مسیر اپلای از آغاز تا پرواز در کنار شما هستیم

🔸ارتباط با ما:
@Dr_Apply

کانال پوزیشن‌ها:
@ApplyTime_Positions

پرداخت ارزی:
@Pay_Time
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Postdoc and senior scientist positions in ML and statistical genetics for neuropsychiatric disease

I have open postdoc and senior scientist positions to work on a National Institute of Mental Health funded project to develop latent factor and network models of ​​neuropsychiatric disease genetics. This multidisciplinary project is a collaboration with Dr. Niamh Mullins at the Icahn School of Medicine at Mount Sinai, an expert in neuropsych genetics and member of the Psychiatric Genomics Consortium.

My lab is joint between the New York Genome Center (NYGC) and Columbia University Computer Science and Systems Biology. We develop probabilistic ML and DL methods for genetics and genomics applications. Beyond this specific project there are opportunities for collaboration with diverse genomics research groups at NYGC and the rich ML/AI community at Columbia and across NYC more broadly.

Official job postings are here (but feel free to email me directly if you are interested!)

Staff Scientist (machine learning and statistical genetics), Knowles Lab

Postdoctoral researcher (machine learning and statistical genetics), Knowles Lab

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David A. Knowles (he/him/his), PhD.
Core Faculty Member, New York Genome Center.
Assistant Professor, Computer Science, Columbia University.

Interdisciplinary Appointee, Systems Biology, Columbia University.

Affiliate Member, Data Science Institute, Columbia University.

https://daklab.github.io/
✔️ @ApplyTime
✔️ @ApplyTime
✔️ @ApplyTime
✔️ @ApplyTime
Imaging and machine learning: Multiple Graduate student positions are available in the area of imaging and machine learning with applications in the tumor microenvironment for a newly funded NIH program. Graduate students will develop novel algorithms and software to identify biomarkers of tumor response based on multiplexed spatial and high dimensional discrete genomic data. Spatial data are collected from both 2D- and 3D-microscopy. This is a great opportunity to learn about state-of-the-art large-scale data that are generated from modern instruments and to develop novel methods for their analysis. Applicants must have a master's degree in computer science or engineering with solid programming skills in Python or related languages. Interested applicants should send their CV to bparvin@unr.edu with the Subject heading "Prospective Student."
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