Materials Handling jobs at Microsoft in Taiwan, Taoyuan City

A materials science research position at the interface of ML accelerated materials discovery and synthesis, focusing on simulations of materials and interfaces, for AI Infrastructure.

This is a

The role will focus on developing and improving simulation workflows for amorphous and crystalline materials, including using the MatterSim model and high-throughput data generation pipelines. You will work closely with researchers and experimentalists in materials science, AI, and simulation, contributing to advancing simulation methods for complex materials, including the development of new approaches for modelling atomic interactions, generating and analysing amorphous and interfacial structures, and implementing high-throughput workflows. You will contribute to building robust datasets, improving model accuracy, and enabling systematic exploration of material properties to support innovative materials design and

Required:

• PhD in Materials Science, Solid-state Physics, Computational Chemistry, or a related field, or equivalent training and experience in research.
• Strong background in theoretical and computational material science.
• ExperiencewithDFT methods and workflows.
• Strong software development skills (e.g. in Python)
• Excellent written and verbal communication skills.
• Ability to work independently and as part of a cross-disciplinary team.
• Experience with molecular dynamics simulation.

Preferred Qualifications:

• Familiarity with phase-change materials, thin-film materials, or device physics.
• Experience with solid-solid interface simulations.
• Experience with high-throughput simulation workflows.
• Familiarity with DFT methods for optical properties.
• Experience with amorphousphase simulationsand analysis.
• Understanding of free energysimulationmethodssuch as meta-dynamics.
• Experience working with experimental collaborators and with automated laboratory environment.
• Demonstrated communication skills through impactful academic publications.

• Development of advanced simulation workflows for complex materials and interfaces.
• Develop and refine computational models for atomic-scale interactions and material properties.
• Contribute to the creation and curation of datasets supporting model development and validation.
• Collaborate within a multidisciplinary team—including experts in machine learning, storage materials, and experimental science—to enhance methods for analysing and predicting material behaviour.
• Support the implementation of scalable, automated approaches for materials discovery and characterisation.
• Communicate research progress and contribute to scientific publications and presentations.

Required:

• PhD in computational materials science, computational chemistry, condensed matter physics, machine learning, or related area, or comparable industry experience.
  
• Experience in developing high-throughput DFT workflows and scaling them to tens of thousands of materials.
  
• Proficiency in collaborative code development in Python on shared codebases.
  
• Publication track record in relevant academic journals (npj computational materials, Nature Materials, PRB, PRL, etc.).
  
• Ability to work in an interdisciplinary collaborative environment, through effective communication of technical concepts to non-experts from different technical backgrounds.

Preferred:

• Practical experience with cloud platforms such as Azure, AWS, or Google Cloud.
  
• Experience in designing and producing computational materials datasets.
• Strong understanding of density functional theory and its application in simulating the electronic, magnetic, and optical properties of solid-state materials.
  
• Strong understanding of sampling methods (e.g., molecular dynamics, Monte Carlo methods) and their application in simulating solid-state materials.

• Design and generate novel datasets for training deep learning models for materials design.
• Develop and deploy scalable DFT workflows for large scale data generation.
• Manage and enhance data infrastructure to support scalable and efficient data generation workflows.
• Validate the accuracy and physical correctness of DFT simulation results.
• Prepare technical papers, presentations, and open-source releases of research code.

As a Microsoft Data Center Inventory & Asset Technician (DIAT), you will perform cycle audits, execute incoming/outgoing deliveries, , and document inbound and outbound deliveries. This opportunity will allow you to deepen your knowledge of inventory management principles, warranty process management, data bearing device destruction and advance your career in the process.

Required/minimum qualifications

• High School Diploma AND 6 months experience or an internship in inventory management, retail, warehouse management, or a related field
  • OR equivalent experience.
• Business level fluency to read, write and speak English.
• Ability to work 12-hour shifts, including shift assignments during non-standard business hours that may include evening, nighttime, weekends and/or holidays.
• As indicated, in the job description, this role has a travel requirement of up to 25% which means you may be required to travel, from time to time, as part of this role.

Background Check Requirements:

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:

• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Additional or preferred qualifications

• 2+ years experience in warehouse/supply chain in an information technology (IT) environment, IT, and/or logistics, operating heavy-load movement equipment (e.g., forklift, pallet jacks, chassis lifts) for a large corporation
  • OR equivalent experience.

DIAT ATR-B

DIAT ATR-C

• Embody ourand.

Required:

• PhD in machine learning, computational materials science, or related area, or comparable industry experience.
  
• Experience in developing machine learning force fields.
  
• Proficiency in collaborative code development in Python on shared codebases.
  
• Publication track record in relevant academic journals (npj computational materials, PRB, PRL, etc.) or top-tier conferences (NeurIPS, ICML, ICLR, etc.).
  
• Ability to work in an interdisciplinary collaborative environment, through effective communication of technical concepts tonon-experts from different technical backgrounds.

Preferred:

• Experience in developing large scale foundational machine learning force fields.
  
• Experience in evaluating machine learning force fields for real-world tasks.
  
• Experience in designing and producing large scale datasets for machine learning force fields.

• Design and implement novel neural network architectures for training foundational machine learning potentials.
• Improve the inference speed of machine learning potentials and scale them to large systems.
• Design and implement pipelines to evaluate machine learning potentials for real-world tasks.
• Design and generate novel datasets for training foundational machine learning potentials.
• Prepare technical papers, presentations, and open-source releases of research code.

Required/minimum qualifications

• High School Diploma AND 2+ years experience in warehouse/supply chain in an information technology (IT) environment, logistics, supply chain, inventory management, retail, or a related field
  • OR equivalent experience.
• Ability to work 12-hour shifts, including shift assignments during non-standard business hours that may include evening, nighttime, weekends and/or holidays.
• As indicated, in the job description, this role has a travel requirement of up to 25% which means you may be required to travel, from time to time, as part of this role.
• Business level fluency to read, write and speak English.

Background Check Requirements:

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:

• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Additional or preferred qualifications

• 3+ years experience in warehouse/supply chain in an information technology (IT) environment, IT, and/or logistics, operating heavy-load movement equipment (e.g. forklift, pallet jacks, chassis lifts) for a large corporation
  • OR equivalent experience.

Microsoft will accept applications for the role until September 2, 2025.

• Embody our and .

You will be tasked to use your breadth of knowledge in materials physics, thin-films, and optics to develop techniques to design and prototype next generation materials for cloud infrastructure applications. You will be required to envisage, design, and model new thin-film materials, and then validate these designs by experimentally fabricating and characterising their properties.

You will work with researchers in materials, optics, electronics, machine learning and computer science, feeding back results and experience as well as learning about, considering, and understanding the additional constraints to find good solutions to difficult problems.

Required:

• Undergraduate or Master level degree in physics, materials science, or a closely related field.
• Currently enrolled in a PhD program with at least 12 months experience researching materials.
• A demonstratable record working at the interface of different research fields - especially materials and optics.
• Experienced in physics of materials and their interaction with light.
• Strong analytical skills and experience in data recording, processing and interpretation.
• Ability to work independently and collaboratively in interdisciplinary teams.
• Excellent communication skills in English, both written and spoken.

Preferred Qualifications (zero or more of):

• Knowledge and background in thin-film growth methods.
• Hands-on experience with physical vapor deposition systems for thin film fabrication.
• Hands-on experience with optical lab components and instruments (e.g., lasers, free-space assemblies, optical microscopy systems).
• Experience in atomistic (e.g. DFT) and electromagnetic (e.g. FDTD) modelling.
• Experience designing and using free-space optical systems.
• Ability to program in Python.
• Knowledge of machine learning approaches or materials analysis or process optimisation.

Specific responsibilities during the internship may include:

• Design and execute thin-film deposition experiments using physical vapour deposition (PVD) techniques to fabricate functional materials.
• Characterise deposited films using a suite of analytical tools, such as X-ray fluorescence (XRF), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM), scanning electron microscopy (SEM), Raman, and atomic force microscopy (AFM).
• Collaborate across disciplines, including chemistry, physics, computer science, and machine learning, and contribute to joint research efforts with internal partners.
• Contribute to the presentation of research findings, in internal meetings or reports, or towards the preparation of submissions to peer-reviewed journals.
• Maintain and troubleshoot vacuum systems and diagnostic equipment, ensuring reliable operation of sputtering machines and characterisation instruments.

• High School Diploma AND 2+ year(s) experience warehouse/supply chain in an information technology (IT) environment, inventory management, retail, warehouse management, or a related field

• • OR equivalent experience.

Background Check Requirements:

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:

• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

While not required, we also look for the following
Qualifications:

• 3+ year(s) experience in warehouse/supply chain in an information technology (IT) environment, IT, and/or logistics, operating heavy-load movement equipment (e.g., forklift, pallet jacks, chassis lifts) for a large corporation
  • OR equivalent experience.

Responsibilities

• Prioritize ticketing queues, work to resolve escalations, and clear blocking issues to enable continued
• Provide task specific guidance to a team of technicians responsible for preparing and executing incoming/outgoing deliveries and documenting inbound/outbound packages (e.g. purchase order [PO] receiving, Rack Movement Supervisor [RMS] activities).
• Coordinate with external stakeholders including third-party warehouses, Original Equipment Manufacturer (OEM) vendors, and suppliers as necessary to facilitate inbound and outbound deliveries.
• Perform assigned tasks and escalate issues during high-volume work activity or escalation-based situations.
• Leverage process knowledge and technical skills to resolve escalations (or further escalate if needed), clear blocking issues, and may enable on site and/or remote data center support activities.

• Maintain a strong stakeholder focus to improve quality and ensure that the customer receives the highest return on their investment.

• Ensure teams maintain and perform steps required to keep the inventory balance accurate.

• Act as the Subject Matter Expert (SME) about the Return Merchandise Authorization (RMA) warranty process ensuring teams process failed vendor hardware devices using tools and processes RMAs.

• Manage schedule of DBD destruction or shredding in partnership with senior leadership and ensure team is following all processes and procedures to perform DBD destruction.

• , rack moving, heavy-equipment usage, lifting, ladder/rolling stair use).

• Seek out opportunities to contribute to workstreams and evolve existing workstream processes, services, and solutions toward greater simplification and automation.
• Embody our and .