Phd Researcher, Machine Learning for Construction
Autodesk
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This role on the market
603 open construction roles across 40 companies are on ApplySarthi right now, most of them in Mumbai (4), Hyderabad (4), Delhi NCR (4).
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What construction roles keep asking for: Excel (15%), AWS (13%), Supply chain (12%) — counted across their open postings here.
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Interviews for construction roles keep coming back to Excel, AWS, Supply chain. Practise those questions before you sit with Autodesk.
Questions you are likely to be asked
- Why do you want to join Autodesk?
- What is your experience with Machine learning? Tell me one thing you learned the hard way.
- Tell me about a time the data was messy or wrong. What did you do?
- How would you explain your model's result to someone who is not technical?
- What would you check first if a model's accuracy dropped after going live?
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Practise the Phd Researcher, Machine Learning for Construction at Autodesk interview free →Job Requisition ID # 26WD101430 Position Overview Autodesk Research is looking for a PhD Researcher Intern in machine learning to help advance AI for the architecture, engineering, and construction (AEC) industry. AEC projects generate large amounts of data across design, planning, and construction. Our team studies how machine learning and AI can connect this data and learn from them to understand, predict, and reason about how projects unfold. As a Researcher intern, you will own a research problem in this area, scoped to fit your expertise and the team's current direction. You'll collaborate with researchers and industry domain experts, and your work will help shape how Autodesk brings AI to AEC workflows. Responsibilities Research: Define and investigate an open research question in machine learning and AI for AEC data, from problem framing through experiments and results Model development: Design and train AI and machine learning models, including graph-based and temporal models, on large, heterogeneous real-world project data Uncertainty and evaluation: Build predictive models with reliable uncertainty estimates, and evaluate them rigorously against strong baselines Data preparation: Prepare, integrate, and validate data from multiple sources, including knowledge graph representations Communication: Document methods and results, present findings, and potentially contribute to research publications You will work as an individual contributor within a research team Minimum Qualifications Currently pursuing a PhD in Computer Science, Machine Learning, Data Science, Civil Engineering, Construction Informatics, or a related field with a graduation date no sooner than April 2027. Research experience in graph machine learning on heterogeneous knowledge graphs, including graph neural networks, graph transformers, link prediction, node classification, and graph self-supervised learning (e.g., masked graph autoencoders, joint-embedding predictive architectures (JEPA)) Experience with temporal or time-varying data, through temporal graph models or time-series forecasting Experience with uncertainty-aware prediction, including calibrated probability estimates and learning from small or imbalanced labeled data Rigorous experimental practice: baselines, ablations, leakage-safe train/test splits, and label quality checks Proficiency in Python and PyTorch (PyTorch Geometric or DGL a plus), and graph query languages Self-directed, with the ability to explain technical results clearly to both technical and non-technical audiences Preferred Qualifications Time-series, state-space, or multimodal modeling, including combining time-varying signals from multiple sources and modalities Bayesian or probabilistic modeling Natural language processing or large language models for classifying or extracting information from technical text and AEC data Experience with AEC data or workflows, such as building models, drawings, project schedules, project records, or design review, etc. Knowledge graph engineering: Neo4j/Cypher, ontologies, entity linking, and data integration Publications at top machine learning venues (e.g., NeurIPS, ICML, KDD) or construction computing venues (e.g., Automation in Construction, ASCE computing journals, ISARC, CIB W78) About the Research Intern Program (US) The 2027 Research Internship Program is a 12-week paid program running from Feb 1st to April 30, 2027. You’ll contribute to meaningful projects, learn from industry leaders, and take part in tech talks and development opportunities. Internships align with Autodesk’s Flexible Workplace approach, supporting office, remote, and hybrid work based on business and team needs. Learn More About Autodesk Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made. We take great pride in our culture here at Autodesk – it’s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world. When you’re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us! Salary Transparency Salary is one part of Autodesk’s competitive compensation package. Offers are based on the candidate’s experience, educational level, and geographic location, and can exceed this range. For U.S.-based roles, we expect a starting annualized intern base salary to be between: $47,840 and $95,680 (undergraduate students) $72,800 and $118,500 (Masters/MBA students) $118,560 and $162,240 (PhD students) Equal Employment Opportunity At Autodesk, we're building a diverse workplace and an inclusive culture to give more people the chance to imagine, design, and make a better world. Autodesk is proud to be an equal opportunity employer and considers all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender, gender identity, national origin, disability, veteran status or any other legally protected characteristic. We also consider for employment all qualified applicants regardless of criminal histories, consistent with applicable law. Belonging We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/global-belonging In-Person Onboarding and Identity Verification This role may require in-person onboarding and/or in-person ID verification.
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