Do you enjoy solving algorithm design problems for semiconductor metrology industry, with demanding time, accuracy, and memory requirements ? Do you like to use your creativity, your in-depth knowledge of the machine learning principles, and your hands-on experience with practical problem solving, being part of a highly talented group of algorithm experts ?
Within ASML the sector Development & Engineering is responsible for the development, specification and design of new ASML products. The Business Line Applications provides integrated solutions with computational, metrology and control technology. These solutions extend and improve the performance of lithography and patterning products for the semiconductor industry.
Within D&E Applications, the group YieldStar Algorithms and Physical Modeling covers the development of models and methods required to infer physical model parameters from optical scatterometry data. Relevant new metrics, as well as new measurement functions, with optimum performance characteristics using the raw acquisitions are identified, designed and implemented. The group secures the ASML Competency of Applied Mathematics for Parameter Estimation.
Propose solutions for statistically correct parameter inference, machine learning and optimization algorithms, and system calibrations, which improve semiconductor metrology and enable control solutions.
Communicate crystal clearly on the mathematical principles, algorithm solutions and physical models to stakeholders, without omitting the essentials.
Design and realize fully functional proof-of-concept subsystems on the edge of system specifications, costs and project planning, thereby contributing directly to products for B2B customers world-wide.
Review technical analyses from the team, and structure team contributions keeping the overview.
Consolidate technical-team identity in communication with other departments.
Interfacing with the Research and On-Product Applications groups, while developing the best metrology solutions and a well-founded vision on semiconductor metrology.
Contribute to technical product roadmaps and generate intellectual property protecting ASML products.
Working as a team with similar-minded people, benefitting from each others specific competences.
Ph.D. in Computer Science, Electrical Engineering, Physics, or Applied Mathematics
Excellence in numerically stable modeling, optimization algorithms, and code development
Experience in machine-learning techniques, in developing local and global optimization algorithms, and in applying them to physical problems
Strong expertise in design for manufacturability, stochastic programming and robust optimization
Ability to explain complex physical models and algorithms in a crisp way, without omitting the essentials
Sound understanding of the fundamentals such as linear algebra, probability theory, (non-)parametric Bayesian and (deep) learning methods
Drive creative solutions skills, capable of having the a big picture ( with the product and customer in mind)
Decisive and self-initiating skills, able to workin an ambiguous environment
Able to influence without power
Pragmatic approach and pro-active attitude, with result focus and a can do spirit.
Context of the position
The position is available within the group YieldStar Algorithms and Physical Modeling, Business line Applications.
Keywords: parameter inference, deterministic and robust optimization, (non-)convex optimization, Kriging, deep learning, supervised learning, reinforcement learning, Gaussian process, neural network, Kriging, Bayesian optimization, inverse problems, surrogate modeling, classification and regression, stochastic programming, physical modeling, physical calibration, information theory