Sort by
Refine Your Search
-
identified by human’s ability to work with new material (Stone Age, Bronze Age), today our abilities and projects span a variety of materials and combine everything from physics and chemistry to civil and
-
identified by human’s ability to work with new material (Stone Age, Bronze Age), today our abilities and projects span a variety of materials and combine everything from physics and chemistry to civil and
-
, bio-engineering, physics, material, and chemical engineering. The mission is to bring the state-of-the-art machine learning algorithm to mechanical engineering. Core responsibilities include: Developing
-
interests, including mechanical, computer science, bio-engineering, physics, material, and chemical engineering. The mission is to bring the state-of-the-art machine learning algorithm to mechanical
-
technical discipline, preferable computer science, electrical engineering, or mechanical engineering. Required Skillsets (proficiencies, competencies, research, software skills. Problem solving skills
-
university’s creative, dedicated, and close-knit community. We place emphasis on practical problem solving, interdisciplinary learning, a visionary spirit, and collaboration. The Computer Science Department (CSD
-
experience 0-1 year of research experience Training: OSHA - Hazardous Materials Safety Training Joining the CMU team opens the door to an array of exceptional benefits available to eligible employees. Those
-
University. Candidates should have experience with molecular biology and AAV design and production, small animal surgery including stereotaxic brain injections, a background in bioinformatics and the ability
-
beamline at the Advanced Light Source in Berkeley, CA. ·Applicants must have a Ph.D. in physics/material science or related field of experience. · Candidate must have experience in working independently
-
Details Posted: 11-Mar-24 Location: Pittsburgh, PA Salary: Open Categories: Academic/Faculty Internal Number: 122412 Introduction The Technology for Effective and Efficient Learning (TEEL) Lab