221 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions at Nature Careers in United States
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Senior Bioinformatics Research Scientist - Northcott Lab in the Center of Excellence in Neuro-Oncolo
, epigenomics, single-cell, spatial 'omics, machine learning, and artificial intelligence. Experience in analyzing, interpreting, and visualizing human genomics datasets generated by high-throughput sequencing
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computational analysis, deep learning, and calcium imaging–based approaches. We work primarily with the model system C. elegans and apply both computational and experimental methods to uncover fundamental
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, police organization, military branch, conflict counselling) required. Some experience in data entry and working in emergency situations and fast pace stressful environment, standing for long hours and
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development of modern AI and machine learning techniques. The successful candidate will have a shared appointment in both the Department of Civil and Environmental Engineering (CEE) and the Schwarzman College
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, computational biology, systems immunology, machine learning, functional genomics, molecular and single-cell biology, metabolic network and whole-cell modeling, or innovative methods for generating, analyzing, and
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survivorship programs in the world. We provide advanced, specialized training on the spectrum of late effects of cancer therapy. You will learn to recognize at-risk cancer survivors by performing risk-based
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collecting relevant data from 2D, 3D or 4D images. Perform computer automated analysis and quality control on large data sets. Liaise effectively with other groups at Janelia to manage multiple image analysis
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Faculty Positions in Genomics and Bioinformatics at the Institute for Genome Sciences, University of
translational biomedical research. We especially encourage applicants with research programs focused on developing machine learning / AI methods for bioinformatics, subclone and mutational analysis, genome
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databases of observed ground motions, physics-based simulations of seismic waveforms and cutting-edge machine learning methods. This next generation of models should account for potential nonlinear site
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for antibody repertoire sequencing and AI-driven research initiatives. Lead the integration of NGS into discovery workflows (in-vivo and in-vitro), emphasizing data generation for machine learning applications