Senior Algorithm Engineer (Phase Retrieval)

AIM Solutions; Eindhoven; On-site; EUR 90,000 - 150,000; Full time

Benefits offered by this job

Ownership of algorithms

Small team with real impact

Competitive Dutch salary

Job summary

AIM Solutions in Eindhoven seeks a senior researcher to own the GPU-accelerated phase retrieval engine for wafer metrology. You’ll drive reconstruction quality, convergence, and robustness across imperfect data, translating literature into robust, tested code and shaping algorithms with physics-based forward models.

You will leverage Fourier optics knowledge, Python and GPU frameworks to optimize performance on large datasets, joining a small, ambitious team in a deep-tech startup.

Qualifications

• PhD or equivalent research depth in a physics-heavy or numerically heavy field.
• Several years developing numerical or scientific algorithms, ideally in imaging, inverse problems, or a comparable domain.
• Strong numerical optimization, both gradient-based and iterative methods.
• Working knowledge of Fourier optics and wave-propagation physics.
• Strong Python and array programming with GPU frameworks (JAX, PyTorch, TensorFlow, CUDA).
• Code should be tested and maintainable for use by others in a real instrument.
• Ability to reason from physics to algorithm and back to improve reconstructions.
• Full professional proficiency in English.

Responsibilities

• Own and evolve the GPU-accelerated computational imaging engine for phase retrieval.
• Improve reconstruction quality, convergence, and robustness across varied datasets.
• Design new reconstruction methods: differentiable forward models, regularization and constraints for ill-posed problems.
• Translate literature and ideas into tested, performant code.
• Use physical insight into the optical system to steer algorithm improvements.
• Profile and optimize the engine for GPU performance on large datasets.

Skills

PhD or equivalent

Numerical algorithms

Numerical optimization

Fourier optics

Python & GPU

Tested maintainable code

Physics-to-algorithm reasoning

English proficiency

Education

PhD in physics or numerically heavy field

Tools

JAX

PyTorch

TensorFlow

CUDA

Job description

About us

AIM Solutions is an early-stage deep-tech startup in Eindhoven building inspection and metrology equipment for the semiconductor industry. We are in active build phase, small, and growing.

The role

You will own the algorithms at the core of our instrument: the GPU-accelerated engine for phase retrieval and wafer metrology. This is the deep end of computational imaging, where progress comes from understanding both the optimization and the physics.

Concretely, you will:

• Develop and maintain our GPU-accelerated computational imaging engine for phase retrieval

• Improve reconstruction quality, convergence, and robustness across varied and imperfect datasets

• Design and implement new reconstruction methods: physics-based differentiable forward models, regularization and constraint schemes for ill-posed problems, and support for new acquisition modes

• Translate methods from the literature and from our own ideas into tested, performant code

• Use physical insight into the optical system to decide how to change the algorithm so that results improve

• Profile and optimize the engine for GPU performance on large datasets

Your profile

• A PhD, or equivalent research depth from industry, in a physics-heavy or numerically heavy field

• Several years developing numerical or scientific algorithms, ideally in imaging, inverse problems, or a comparable domain

• Strong numerical optimization, both gradient-based and iterative methods

• Working knowledge of Fourier optics and wave-propagation physics

• Strong Python and array programming, with experience in GPU frameworks such as JAX, PyTorch, TensorFlow, or CUDA

• You write tested, maintainable code that others can build on

• You can reason from physics to algorithm and back, and judge what will improve a reconstruction

• Technical curiosity; we will teach you the specifics of our computational imaging approach

• Full professional proficiency in English

Bonus experience in any of these:

• Phase retrieval, coherent diffractive imaging, holography, or tomography

• Physics-informed machine learning, differentiable forward models, automatic differentiation

• Regularization and constrained optimization for ill-posed inverse problems

• High-performance and GPU computing with performance profiling

• Linux development environments

This is a senior, research-to-production role. We expect a track record of taking new methods from concept to working, maintained code that runs in a real instrument.

What we offer

• Ownership of the reconstruction algorithms at the heart of a tool that does not exist anywhere else yet

• Small team, short feedback loops, an open environment to have real impact

• Competitive salary for the Dutch market