41 machine-learning "https:" "https:" "https:" "https:" "https:" research jobs at Nature Careers
Sort by
Refine Your Search
-
Listed
-
Country
-
Program
-
Field
-
uses long timescale molecular dynamics (MD) simulations, integrated with experimental observables (especially cryo-electron microscopy data), and machine learning tools to better capture the dynamics
-
or translational research experience Knowledge of machine learning, Bayesian modeling, or statistical method development Ideal Personal Attributes: Independent, proactive, and scientifically curious Detail-oriented
-
involve directed evolution and protein optimisation, applying molecular biology and biophysics. Researchers will be supported to develop skills in the latest AI or machine learning tools for protein design
-
, Electrical Engineering, Aerospace Engineering or a related field, with a focus on Robotic Perception and learning based methods Demonstrated expertise in at least one of the following areas: Machine Learning
-
machine learning or trustworthy AI, including experience with robustness assessment and attack/defense mechanisms. Expertise in software security and code analysis, with understanding of common
-
mathematics, biophysics, AI/machine learning, computational biology, computer science/engineering, statistical inference, or related fields are particularly encouraged to apply. POSITION DESCRIPTION Flatiron
-
networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our
-
Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
-
Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning
-
Project Description: Drug toxicity and resistance are the leading causes of therapeutic failures. The Chen Lab (https://www.stjude.org/research/labs/chen-lab-taosheng.html) studies: (1) the chemical