Mathematician for Geodetic Metrology (BE-GM-APC-2024-157-LD)

Company Description

At CERN, the European Organization for Nuclear Research, physicists and engineers are probing the fundamental structure of the universe. Using the world's largest and most complex scientific instruments, they study the basic constituents of matter - fundamental particles that are made to collide together at close to the speed of light. The process gives physicists clues about how particles interact, and provides insights into the fundamental laws of nature. Find out more on http://home.cern.

Job Description

Introduction

Join the Geodetic Metrology group at CERN, to develop new alignment methods and tools for the Future Circular Collider (FCC) study. You will be part of the team in charge of the development of the R&D for the next generation of colliders. You will actively contribute to build, integrate and support the wide range of computing tools used for metrology and alignment at CERN, with a focus on the theoretical aspects related to the statistical data processing of survey data, the development of mathematical concepts and the proposition of new algorithms responding the future project needs. You will collaborate with other research teams, inside and outside CERN, to benefit from the latest developments in this field. Take part! 

Functions

As a mathematician:  

• You will be part of a research team that develops innovative measurement techniques and new instruments for the next generation of colliders. You will take into account their latest experimental results to elaborate the mathematical models that accurately describe the behaviour of new devices and sensors. 
• You will study more complex measurement systems combining different techniques and types of instrumentation, and you will establish corresponding theoretical models. You will thus contribute to optimizing the configuration of these future measurement systems and finding the best compromises with different experts. You will carry out the complete simulation of different measurement system solutions and evaluate their effectiveness in terms of expected accuracy, reliability criteria and robustness analysis.
•  You will develop and apply parameter estimation techniques, including least squares, L1 norm minimization, and Huber estimation.
•  You will address future challenges related to large-scale optimization, developing scalable solutions that can efficiently handle high-dimensional problems. You will propose innovative solutions to perform the enormous calculations required by simulations, keeping in mind that similar methods could also be integrated into the future operational data processing workflow. 
• You will design real-time estimation algorithms with a strong focus on speed and efficiency to meet the demands of time-sensitive applications such as monitoring tasks. You will also have the opportunity to partly implement some of the most promising results from your studies into today's survey data processing workflow. 
• You will present optimization results and insights to various audiences, including surveying engineers, software experts, and non-expert stakeholders, ensuring that the implications and benefits are clearly understood. You will tailor communication to effectively convey complex mathematical concepts to both technical and non-technical audiences. 

Qualifications

Master's degree or PhD or equivalent relevant experience in the field of Applied Mathematics, Geodesy or Geomatics, with a focus on optimization and parameter estimation or a related field.

Experience:

• Proven ability to understand engineering challenges and translate them into well-defined mathematical problems that capture the essence of issues at hand. 

• Demonstrated experience producing mathematical models and algorithms. Knowledge and practice of standard adjustment software: theories, concepts and algorithms related to the least square adjustment. 

• Relevant experience using numerical libraries such as Eigen or SuiteSparse for handling large sparse matrices and performing QR decompositions. 

• Extensive experience in C++ development, including performance optimization and cross-platform development (Windows and Linux). 

• Demonstrated experience in the data treatment of geodetic measurements, transformations between coordinate reference systems, would be a strong asset. 

Technical competencies:

• Knowledge of programming techniques and languages: in particular (Python, C++), using Git tools for version control and continuous integration;
• Strong theoretical background in parameter estimation methods, including least squares, and robust estimation techniques such as L1 norm minimization and Huber estimation;
• Proficiency in non-linear optimization methods, including Gauss-Newton and other globalization techniques, and deep understanding of linear algebra;
• Theoretical knowledge of high-precision survey methods and tools.

Behavioural competencies:

• Achieving Results:
  • Delivering high quality work on time and fulfilling expectations
  • Having a structured and organised approach towards work; being able to set priorities and plan tasks with results in mind
  • Driving work / projects along and seeing them through to their conclusion
• Solving Problems:
  • Identifying, defining and assessing problems, taking action to address them
  • Finding the information needed to solve problems; making objective judgments based on all the facts available
  • Producing workable and timely solutions that meet requirements;
• Learning and Sharing Knowledge:
  • Keeping up-to-date with developments in own field of expertise and readily absorbing new information
  • Sharing knowledge and expertise freely and willingly with others; coaching others to ensure knowledge transfer
  • Proposing ways to improve or streamline existing procedures, processes and methodologie
• Working in Teams: 
  • Understanding when teamwork is required to achieve the best results; including others accordingly and sharing information
  • Contributing to promoting a positive atmosphere in the team through an optimistic and constructive attitude; addressing issues
  • Cooperating constructively with others in the pursuit of team goals; balancing personal goals with team goals.

Language skills:

Spoken and written English in a professional setting; willingness to learn French.

Additional Information

Eligibility and closing date:

Diversity has been an integral part of CERN's mission since its foundation and is an established value of the Organization. Employing a diverse workforce is central to our success.

This vacancy will be filled as soon as possible, and applications should normally reach us no later than 03.12.2024. at 23.45 CET

Employment Conditions

Contract type: Limited duration contract (5 years). Subject to certain conditions, holders of limited-duration contracts may apply for an indefinite position.

Working Hours: 40 hours per week

Job grade: 6-7

Job reference: BE-GM-APC-2024-157-LD

Benchmark Job Title: Mechanical Engineer

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