Postdoc and PhD Student Positions in Design of High-Temperature Alloys Full-time

The research group at Harbin Institute of Technology invites applications for postdoctoral researchers and PhD students working on the design and development of novel alloys for high-temperature applications.

The project aims to establish an integrated alloy-development framework combining experimental research, computational simulation, machine learning, and data science. Successful candidates will contribute to the full development cycle of high-temperature alloys, including machine-learning-assisted alloy design, computational screening, candidate-alloy selection, material preparation and processing, microstructural characterization, performance evaluation, and application-oriented validation.

Research Scope

The research will focus on one or more of the following areas:

Machine Learning for Alloy Design

Development and application of machine-learning and data-driven models for alloy composition design, phase and microstructure prediction, property prediction, multi-objective optimization, uncertainty assessment, and inverse design of novel high-temperature alloys.

Computational Simulation of Alloys

Use of computational approaches, including density functional theory, molecular dynamics, and finite element modeling, to investigate phase stability, thermodynamic and mechanical behavior, diffusion, defects, deformation mechanisms, oxidation, fracture, creep, fatigue, and other phenomena relevant to the high-temperature performance of alloys.

Alloy Preparation and Processing

Selection, preparation, and processing of candidate alloys. Relevant processing routes may include casting, powder metallurgy, thermomechanical processing, heat treatment, and additive manufacturing.

Microstructural and Performance Characterization

Characterization of alloy composition, phase constitution, microstructure, defects, and deformation mechanisms, together with evaluation of mechanical, fatigue, and other service-related properties at elevated temperatures.

Candidate Requirements

Strong knowledge of metallic materials and alloys is essential. Applicants should have a solid understanding of alloy composition, phase transformations, microstructure, processing, mechanical behavior, and structure–property relationships.

Candidates are expected to have the following qualifications:

• Expertise in at least one computational simulation method, such as density functional theory, molecular dynamics, or finite element modeling.
• Experience in machine learning, data science, materials informatics, scientific programming, or data-driven materials modeling.
• Proficiency in Python or other programming languages and experience with high-throughput computation, scientific databases, or computational workflow development will be advantageous.
• Experimental experience in alloy preparation, thermomechanical processing, heat treatment, microstructural characterization, or high-temperature mechanical testing will be considered an asset.
• Other expertise relevant to high-temperature alloy development, such as thermodynamic calculations, CALPHAD, phase-field modeling, oxidation and corrosion, creep, fatigue, fracture, additive manufacturing, or advanced characterization, is also welcome.
• Applicants should demonstrate strong research motivation, independent problem-solving ability, effective communication skills, and an interest in interdisciplinary collaboration.

For postdoctoral applicants, a PhD degree in a relevant discipline is required. A strong publication record and demonstrated experience in independent research, project development, proposal preparation, student mentoring, or interdisciplinary collaboration will be advantageous.

For PhD applicants, a strong academic background in materials science, metallurgy, mechanics, physics, chemistry, or a related field is required. Prior research, programming, simulation, machine-learning, or experimental experience is preferred.

What We Offer

The group provides an interdisciplinary research environment integrating alloy theory, computational simulation, artificial intelligence, materials processing, experimental characterization, and performance evaluation.

Successful candidates will have opportunities to:

• Participate in the development of novel alloys for demanding high-temperature applications;
• Work across machine learning, computational simulation, alloy processing, and experimental validation;
• Access advanced computational and experimental research facilities;
• Collaborate with national and international research partners;
• Publish research findings in high-quality international journals;
• Develop expertise in both computational and experimental alloy design; and
• Receive competitive financial support and opportunities for professional and career development.

Application Procedure

Applicants should submit the following materials as PDF file:

• A cover letter describing their research background, relevant expertise, research interests, and suitability for the position;
• A detailed curriculum vitae, including education, research experience, technical skills, publications, and other relevant achievements.

Postdoctoral applicants are also encouraged to include a brief description of their proposed research direction and contact information for two or three academic referees.

Applications should be sent to:

hcchen2100 at gmail.com

Tagged as: Engineering