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Postdoctoral Scholar-Skillset 2 at Alfred University
Alfred, New York, United States -
Full Time

Start Date

Immediate

Expiry Date

03 Mar, 26

Salary

0.0

Posted On

04 Dec, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Ultra High Temperature Ceramics, Material Synthesis, Machine Learning, Data-Driven Discovery, High-Throughput Experiments, Unsupervised Machine Learning, Deep Learning, Materials Characterization, High Entropy Ceramics, Data Generation, Algorithm Training, Properties Studies, Collaboration, Research, New Materials Discovery, High-Quality Data

Industry

Description
Alfred University seeks qualified applicants to work in the area of ultra high temperature ceramic synthesis, processing and characterization. The project spans 5 individual project areas, with postdoctoral research associates needed with the following skillset: New materials discovery aided by Al/ML fields, will engage in high-throughput synthesis and properties studies guided by machine learning. The position will center on data-driven discovery and characterization of high entropy ultra-high temperature ceramics. The successful candidate will be expected to work to extend our expertise in high-throughput experiments to generate high-quality and reliable data for machine learning modeling. Un/supervised machine learning and deep learning will be used to train the algorithms and predict the resulting structures and properties. Selected compositions will be selected for further materials fabrication and characterization. The PORA will work closely with faculty, other postdocs, laboratory technicians, graduate students and scientists from outside laboratories. Alfred University actively subscribes to a policy of equal employment opportunity, and will not discriminate against any employee, student or applicant because of race, age, sex, color, sexual orientation, gender identification or expression, physical or mental disability, religion, ancestry or national origin, marital status, genetic information, military or veteran status, domestic violence victim status, criminal conviction status, political affiliation or any other characteristic protected by applicable law.
Responsibilities
The successful candidate will engage in high-throughput synthesis and properties studies guided by machine learning. They will work closely with faculty, other postdocs, laboratory technicians, graduate students, and scientists from outside laboratories.