荷兰代尔夫特理工大学2023年招聘博士后职位（基于贝叶斯机器学习的组合设计）

代尔夫特理工大学（Technische Universiteit Delft，简写TU Delft）始建于1842年，位于荷兰代尔夫特市，前身为荷兰王国皇家学院，欧洲顶尖工科联盟IDEA联盟战略成员，仅专注于工程技术领域，是荷兰历史悠久、规模庞大的工科院校。

Postdoc Composite Design with Bayesian Machine Learning

Delft University of Technology

Netherlands

October 29, 2023

Contact:N/A

Offerd Salary:欧元3,226

Location:N/A

Working address:N/A

Contract Type:Other

Working Time:Negotigation

Working type:N/A

Ref info:N/A

Postdoc Composite Design with Bayesian Machine Learning Apply Now

Explore and develop scalable Bayesian machine learning methods for aerospace structures

Job description

This postdoctoral research aims at exploring statistical methods that enable the data-driven analysis and design of aerospace composite structures. The candidate should have a background in Statistics, Uncertainty Quantification, or Bayesian machine learning methods, and is motivated to apply these methods to solve Engineering problems. The candidate will be working in the CAELESTIS project including a team of experimentalists; therefore, interaction with these colleagues is expected. The research group hosting this candidate includes experts in simulation and machine learning methods, but it is currently lacking proficiency in Statistics and uncertainty quantification. The postdoc will be rewarded with significant independence, and is expected to help supervise one PhD student working on the topic. Additional details can be provided during the interview. There is some flexibility concerning the type of methods to explore, depending on the interests and expertise of the candidate (within reasonable bounds!).

CAELESTIS main objective is to enable the EU aircraft industry to design and manufacture disruptive aircraft structures and engines with enhanced prediction capacities (product performance and manufacturability), to widen the design space and reduce the uncertainties potentially encountered along the product and engineering lifecycle, which are currently limiting their introduction into service.

Requirements

Applicants must have the following qualifications:

· Strong computational skills.

· Strong background in statistics or related field.

· A background in mechanical/aerospace/civil engineering, materials science, physics or a related area is a plus.

· Proficiency with machine learning methods and corresponding software packages.

· An interest in applying these methods to modeling mechanics and/or manufacturing of composites (past experience is a plus, but not required).

· The ability to work well in a collaborative setting.Conditions of employment

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities (based on scale 10: 欧元3,226.00 - 欧元5,090.00). The contract of employment is offered for two years. The position is open for 36-40 hours per week. The TU Delft offers a customisable compensation package, a discount on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants, TU Delft has the Coming to Delft Service. This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.

TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

Faculty Aerospace Engineering

The Faculty of Aerospace Engineering at Delft University of Technology is one of the world's most highly ranked (and most comprehensive) research, education and innovation communities devoted entirely to aerospace engineering. More than 200 science staff, around 270 PhD candidates and close to 3000 BSc and MSc students apply aerospace engineering disciplines to address the global societal challenges that threaten us today, climate change without doubt being the most important. Our focal subjects: sustainable aerospace, big data and artificial intelligence, bio-inspired engineering and smart instruments and systems. Working at the faculty means working together. With partners in other faculties, knowledge institutes, governments and industry, both aerospace and non-aerospace. Working in field labs and innovation hubs on our university campus and beyond.

Click here to go to the website of the Faculty of Aerospace Engineering.

Additional information

For more information about this vacancy, please contact Dr. Baris Caglar, Assistant Professor at Faculty of Aerospace Engineering (co-supervising candidate in person), email: B.Caglar@tudelft.nl or Dr. Miguel Bessa, Associate Professor at Brown University (co-supervising candidate remotely), email: miguelbessa@brown.edu. Temporary stays at Brown University with the Bessa group are possible, in case the candidate is interested.

For more information about the application procedure, please contact recruitment-lr@tudelft.nl.

Application procedure

Are you interested in this vacancy? Please apply before 29 October 2023 via the application button and upload your motivation and CV.

· A pre-employment screening can be part of the selection procedure.

· You can apply online. We will not process applications sent by email and/or post.

· Please do not contact us for unsolicited services.

Faculty/Department

Faculty of Aerospace Engineering

Job Type

Postdoc Positions

Scientific field

Engineering

Hours per week

36-40

Salary

欧元 3.226,00 - 欧元 5.090,00

Desired level of education

Doctorate

Vacancy number

TUD04334

Method of applying

Via system

Explore and develop scalable Bayesian machine learning methods for aerospace structures

Job description

This postdoctoral research aims at exploring statistical methods that enable the data-driven analysis and design of aerospace composite structures. The candidate should have a background in Statistics, Uncertainty Quantification, or Bayesian machine learning methods, and is motivated to apply these methods to solve Engineering problems. The candidate will be working in the CAELESTIS project including a team of experimentalists; therefore, interaction with these colleagues is expected. The research group hosting this candidate includes experts in simulation and machine learning methods, but it is currently lacking proficiency in Statistics and uncertainty quantification. The postdoc will be rewarded with significant independence, and is expected to help supervise one PhD student working on the topic. Additional details can be provided during the interview. There is some flexibility concerning the type of methods to explore, depending on the interests and expertise of the candidate (within reasonable bounds!).

CAELESTIS main objective is to enable the EU aircraft industry to design and manufacture disruptive aircraft structures and engines with enhanced prediction capacities (product performance and manufacturability), to widen the design space and reduce the uncertainties potentially encountered along the product and engineering lifecycle, which are currently limiting their introduction into service.

Requirements

Applicants must have the following qualifications:

· Strong computational skills.

· Strong background in statistics or related field.

· A background in mechanical/aerospace/civil engineering, materials science, physics or a related area is a plus.

· Proficiency with machine learning methods and corresponding software packages.

· An interest in applying these methods to modeling mechanics and/or manufacturing of composites (past experience is a plus, but not required).

· The ability to work well in a collaborative setting.Conditions of employment

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities (based on scale 10: 欧元3,226.00 - 欧元5,090.00). The contract of employment is offered for two years. The position is open for 36-40 hours per week. The TU Delft offers a customisable compensation package, a discount on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants, TU Delft has the Coming to Delft Service. This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.

TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

Faculty Aerospace Engineering

The Faculty of Aerospace Engineering at Delft University of Technology is one of the world's most highly ranked (and most comprehensive) research, education and innovation communities devoted entirely to aerospace engineering. More than 200 science staff, around 270 PhD candidates and close to 3000 BSc and MSc students apply aerospace engineering disciplines to address the global societal challenges that threaten us today, climate change without doubt being the most important. Our focal subjects: sustainable aerospace, big data and artificial intelligence, bio-inspired engineering and smart instruments and systems. Working at the faculty means working together. With partners in other faculties, knowledge institutes, governments and industry, both aerospace and non-aerospace. Working in field labs and innovation hubs on our university campus and beyond.

Click here to go to the website of the Faculty of Aerospace Engineering.

Additional information

For more information about this vacancy, please contact Dr. Baris Caglar, Assistant Professor at Faculty of Aerospace Engineering (co-supervising candidate in person), email: B.Caglar@tudelft.nl or Dr. Miguel Bessa, Associate Professor at Brown University (co-supervising candidate remotely), email: miguelbessa@brown.edu. Temporary stays at Brown University with the Bessa group are possible, in case the candidate is interested.

For more information about the application procedure, please contact recruitment-lr@tudelft.nl.

Application procedure

Are you interested in this vacancy? Please apply before 29 October 2023 via the application button and upload your motivation and CV.

· A pre-employment screening can be part of the selection procedure.

· You can apply online. We will not process applications sent by email and/or post.

· Please do not contact us for unsolicited services.