577 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" positions at Nature Careers
Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
engineering, aerospace design and manufacturing, flight mechanics and dynamics, propulsion, and/or aerospace numerical methods including machine learning, in a university of similar standing to the University
-
building projects required. Experience with computer-aided drafting (AutoCAD) and Microsoft Office (e.g., Excel, Word, PowerPoint). Familiarity with current technical environmental impact assessment
-
, religion, sex, gender identity or expression, national origin, sexual orientation, genetic information, disability, age, ancestry, military service, protected veteran status, or other characteristics
-
fellows at the University of Tennessee Health Science Center. Fellows receive a competitive salary, professional development allowance, a personal computer for use during the fellowship, tuition assistance
-
to learn it once in position through the French language learning support program offered by the University, according to the Language Policy of the Université de Montréal. How to Apply The application must
-
machine learning methods. The successful candidate will lead an independent research project dedicated to identifying abnormal behavior and neuronal activities in circuits of murine models of 22q11.2 and
-
, advanced communication devices, advanced manufacturing, microfluidics, and more. 3) Intelligent and Bionic Systems: Molecular machines, adaptive micro-/nano-robots, bio-inspired systems, wearable electronics
-
high-dimensional, dynamic, networked system, applying techniques from machine learning, causal inference, statistics, and algorithms. No prior biomedical training is required—just strong quantitative
-
receive a professional development allowance, research allowance, a personal computer for use during the fellowship, tuition assistance, dependent care assistance, moving allowance, an employer-contributed
-
weaknesses in the ability of pathogenic bacteria to evolve resistance to antibiotics. Working at the interface of genetics, chemical biology, and machine learning, we discover and use small molecules