Diagnostics Machine Learning Expert

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

In ASML’s Research department, innovative approaches for diagnosing our complex Lithography systems are developed. These approaches combine data mining, anomaly detection, machine-learning and ASML Lithography scanner knowledge.

Are you challenged by demanding researchprojects in a multidisciplinary context? Do you have the technical capabilities to provide innovative solutions? Does contributing to the world’s most advanced lithography machines makes you feel responsible and proud? Then this might be the right opportunity for you.

Role and responsibilities

This position involves creating novel, data-intensive methods to speed-up and identify the root-cause of ASML scanner failures and to predict future failures.

Responsibilities:

• Within research we look fornovel diagnostic and predictive strategies based on data-mining andmachine learning algorithms.
• Besides this, we areinvestigating ways to combine data with captured field experience andsystem design knowledge, using Bayesian networks and knowledge graphs.
• Using your technical backgroundyou investigate the state of the art data analysis and machine learningstrategies and propose solutions that apply to this problem domain.
• You create predictive anddiagnostic models which you test on actual system data.
• You will interact with otherteams in ASML that work on diagnostics and data-analysis. You invest in anacademic network, define supporting academic research projects.
• The research will be carried out within a multi-disciplinary project-team.

Education and experience

The ideal candidate has a PhD in Data Science, Computer Science or Mathematics with a few years of industrial experience in diagnostics and anomaly detection.

Proven experience in diagnostics of complex industrial systems with the use of various data science, statistical and machine learning methodologies.

Skills

Working at the cutting edge of tech, you’ll always have new challenges and new problems to solve – and working together is the only way do that. You won’t work in a silo. Instead, you’ll be part of a creative, dynamic work environment where you’ll collaborate with supportive colleagues. There is always space for creative and unique points of view. You’ll have the flexibility and trust to choose how best to tackle tasks and solve problems.
To thrive in this job, you’ll need the following skills:

• Solution-oriented, innovativemind-set
• Team-player
• Commitment to team and company
• High personal ambition anddrive
• Drive to deliver excellentperformance
• Self-propelling, independentthinker
• Communication skills forcommunication at various levels in the organization
• Willingness to travel

Diversity & Inclusion

ASML is an Equal Opportunity Employer that values and respects the importance of a diverse and inclusive workforce. It is the policy of the company to recruit, hire, train and promote persons in all job titles without regard to race, color, religion, sex, age, national origin, veteran status, disability, sexual orientation, or gender identity. We recognize that diversity and inclusion is a driving force in the success of our company.

Other information

Context of the position

This project will be carried outat ASML-Research. The project is further part of an intensive collaborationwith other departments within the ASML organization.

This position may require access to controlled technology, as defined in the Export Administration Regulations (15 C.F.R. §730, et seq.). Qualified candidates must be legally authorized to access such controlled technology prior to beginning work. Business demands may require ASML to proceed with candidates who are immediately eligible to access controlled technology.

Other Information:

Diagnostics, anomaly detection , Machine Learning, , Bayesian inference, causality, knowledge graphs, Neural Networks, High Performance Computing (HPC),surrogate models,.