Bemærk at denne jobannonce er udløbet!
Ansøgningsfristen for jobannoncen er overskredet, og stillingen kan ikke længere søges. Opslaget vises udelukkende som reference

Industrial PhD in Predictive Maintenance

Do you want to combine theory with practice and help digitalise our Danish combined heat and power plants? 

Join us and become a PhD student in Digital Products & Processes where you’ll be joining the team of data scientists working with predictive maintenance. We’re looking for a PhD student with the ballast to challenge our current methods and practices.  

Write your PhD with us and get the chance to work on a wide range of complex engineering and scientific challenges. You’ll get the opportunity to work in a large-scale, cross-functional agile setup that we call Smart Plant.  

The Smart Plant initiative has numerous teams working towards a common vision – a digitalised power plant of the future. We want to set the standard for how to operate the power plant of the future through greater mobility, new technology and data.

Project description

As a PhD student in the Smart Plant Predictive Maintenance team you’ll work as a data scientist to pursue your academic ambition. 

The aim of the Smart Plant project is to bring data science and machine learning models into the engineering domain. We’re developing models for surveillance of our critical power plant components. We expect that you’ll be working part time on the Smart Plant initiative, where you’ll have access to data, development environments and a network of data scientists. You’ll have the freedom to spend the remaining time writing your dissertation and pursuing your academic ambition within the field of predictive maintenance.  

As a PhD student, you’ll contribute to maturing and developing the relatively new field of predictive maintenance and data science with the latest academic insight.

Your competences include that you

  • have a master’s degree in mathematics, statistics, computer or data science or other math-heavy education
  • have extensive experience with Python
  • have experience with data handling and model building 
  • have some understanding of industrial processes and production assets or are motivated to learn.

It’s a plus but not a requirement to have basic data engineering skills and understanding of cloud computing platforms such as Azure.

It’s a requirement that you have a supervisor within the field of data science and predictive maintenance. We expect that you have the support for an industrial PhD from your educational institute. In return, we can offer an Ørsted-wide network of data scientists, large data sets across our power plant portfolio and exciting real-life challenges to solve.

Functional area: Predictive Maintenance 

Number of PhD students: One

Academic level: Postgraduate 

Working hours: 37 hours  

Place of work: Gentofte or Skærbæk depending on candidate   

Would you like to help shape the renewable technologies of the future?

Send your application to us as soon as possible and no later than 1 March 2020, as we’ll be conducting interviews on a continuous basis.

Please don’t hesitate to contact Anastasia Fomenko, Manager of Digital Products & Processes and Product Manager of Smart Plant, by telephone on +45 99 55 88 91 if you’d like to know more about the position.

Desired start date: As soon as possible and depending on university deadlines

Additional info: You should expect occasional travel to central power stations around Denmark.

About Ørsted

Headquartered in Denmark, Ørsted’s 6,500 employees develop, construct and operate offshore and onshore wind farms, solar farms and energy storage facilities, bioenergy plants and provide energy products to its customers. In Ørsted Markets & Bioenergy, we’re 1,100 employees ensuring that we have the world’s most flexible and efficient biomass-fired power stations. We also develop, construct and operate new green waste-to-energy solutions and deliver state-of-the-art smart energy solutions to our customers. For more information on Ørsted, visit orsted.com


Mere af samme slags?

Angiv din e-mail og få lignende job direkte i indbakken




Når du tilmelder dig accepterer du samtidig vores privativspolitik

330161855Phoenix-85d71bec12020-01-22T00:00:00Industrial PhD in Predictive Maintenance

Do you want to combine theory with practice and help digitalise our Danish combined heat and power plants? 

Join us and become a PhD student in Digital Products & Processes where you’ll be joining the team of data scientists working with predictive maintenance. We’re looking for a PhD student with the ballast to challenge our current methods and practices.  

Write your PhD with us and get the chance to work on a wide range of complex engineering and scientific challenges. You’ll get the opportunity to work in a large-scale, cross-functional agile setup that we call Smart Plant.  

The Smart Plant initiative has numerous teams working towards a common vision – a digitalised power plant of the future. We want to set the standard for how to operate the power plant of the future through greater mobility, new technology and data.

Project description

As a PhD student in the Smart Plant Predictive Maintenance team you’ll work as a data scientist to pursue your academic ambition. 

The aim of the Smart Plant project is to bring data science and machine learning models into the engineering domain. We’re developing models for surveillance of our critical power plant components. We expect that you’ll be working part time on the Smart Plant initiative, where you’ll have access to data, development environments and a network of data scientists. You’ll have the freedom to spend the remaining time writing your dissertation and pursuing your academic ambition within the field of predictive maintenance.  

As a PhD student, you’ll contribute to maturing and developing the relatively new field of predictive maintenance and data science with the latest academic insight.

Your competences include that you

  • have a master’s degree in mathematics, statistics, computer or data science or other math-heavy education
  • have extensive experience with Python
  • have experience with data handling and model building 
  • have some understanding of industrial processes and production assets or are motivated to learn.

It’s a plus but not a requirement to have basic data engineering skills and understanding of cloud computing platforms such as Azure.

It’s a requirement that you have a supervisor within the field of data science and predictive maintenance. We expect that you have the support for an industrial PhD from your educational institute. In return, we can offer an Ørsted-wide network of data scientists, large data sets across our power plant portfolio and exciting real-life challenges to solve.

Functional area: Predictive Maintenance 

Number of PhD students: One

Academic level: Postgraduate 

Working hours: 37 hours  

Place of work: Gentofte or Skærbæk depending on candidate   

Would you like to help shape the renewable technologies of the future?

Send your application to us as soon as possible and no later than 1 March 2020, as we’ll be conducting interviews on a continuous basis.

Please don’t hesitate to contact Anastasia Fomenko, Manager of Digital Products & Processes and Product Manager of Smart Plant, by telephone on +45 99 55 88 91 if you’d like to know more about the position.

Desired start date: As soon as possible and depending on university deadlines

Additional info: You should expect occasional travel to central power stations around Denmark.

About Ørsted

Headquartered in Denmark, Ørsted’s 6,500 employees develop, construct and operate offshore and onshore wind farms, solar farms and energy storage facilities, bioenergy plants and provide energy products to its customers. In Ørsted Markets & Bioenergy, we’re 1,100 employees ensuring that we have the world’s most flexible and efficient biomass-fired power stations. We also develop, construct and operate new green waste-to-energy solutions and deliver state-of-the-art smart energy solutions to our customers. For more information on Ørsted, visit orsted.com

2020-02-17T19:50:48.680 Do you want to combine theory with practice and help digitalise our Danish combined heat and power plants? Join us and become a PhD student in Digital Products Processes where you ll be joining the team of data scientists working with predictive maintenance. We re looking for a PhD student with the ballast to challenge our current methods and practices. Write your PhD with us and get the chance to work on a wide range of complex engineering and scientific challenges. You ll get the opportunity to work in a large-scale, cross-functional agile setup that we call Smart Plant. The Smart Plant initiative has numerous teams working towards a common vision a digitalised power plant of the future. We want to set the standard for how to operate the power plant of the future through greater mobility, new technology and data. Project description As a PhD student in the Smart Plant Predictive Maintenance team you ll work as a data scientist to pursue your academic ambition. The aim of the Smart Plant project is to bring data science and machine learning models into the engineering domain. We re developing models for surveillance of our critical power plant components. We expect that you ll be working part time on the Smart Plant initiative, where you ll have access to data, development environments and a network of data scientists. You ll have the freedom to spend the remaining time writing your dissertation and pursuing your academic ambition within the field of predictive maintenance. As a PhD student, you ll contribute to maturing and developing the relatively new field of predictive maintenance and data science with the latest academic insight. Your competences include that you have a master s degree in mathematics, statistics, computer or data science or other math-heavy education have extensive experience with Python have experience with data handling and model building have some understanding of industrial processes and production assets or are motivated to learn. It s a plus but not a requirement to have basic data engineering skills and understanding of cloud computing platforms such as Azure. It s a requirement that you have a supervisor within the field of data science and predictive maintenance. We expect that you have the support for an industrial PhD from your educational institute. In return, we can offer an Ørsted-wide network of data scientists, large data sets across our power plant portfolio and exciting real-life challenges to solve. Functional area: Predictive Maintenance Number of PhD students: One Academic level: Postgraduate Working hours: 37 hours Place of work: Gentofte or Skærbæk depending on candidate Would you like to help shape the renewable technologies of the future? Send your application to us as soon as possible and no later than 1 March 2020, as we ll be conducting interviews on a continuous basis. Please don t hesitate to contact Anastasia Fomenko, Manager of Digital Products Processes and Product Manager of Smart Plant, by telephone on 45 99 55 88 91 if you d like to know more about the position. Desired start date: As soon as possible and depending on university deadlines Additional info: You should expect occasional travel to central power stations around Denmark. About Ørsted Headquartered in Denmark, Ørsted s 6,500 employees develop, construct and operate offshore and onshore wind farms, solar farms and energy storage facilities, bioenergy plants and provide energy products to its customers. In Ørsted Markets Bioenergy, we re 1,100 employees ensuring that we have the world s most flexible and efficient biomass-fired power stations. We also develop, construct and operate new green waste-to-energy solutions and deliver state-of-the-art smart energy solutions to our customers. For more information on Ørsted, visit orsted.com.11Jobnet85d71bec100000000000IDK_OFIR_02DKDanmark228DKK2020-03-01T00:00:000000https://orsted.com/en/Careers/Vacancies-list/Hiring-process/Job-List/2020/01/1981720EuropaDanmarkJyllandSyd- og SønderjyllandVejleEuropaDanmarkJyllandSyd- og SønderjyllandFredericia3695741Ørsted A/S11Kraftværksvej 537000FredericiaDKDanmark0DKDanmarkDKDanmark8Fuldtid46Permanent10000889051JobNet5103287510328710021-01-2020000https://dispatcher.ofir.dk/statistic/register?context=FeedEntrySearchedCount&feedId=dc2beb84&entryId=85d71bechttps://dispatcher.ofir.dk/statistic/register?context=FeedEntryDisplayCount&feedId=dc2beb84&entryId=85d71bechttps://dispatcher.ofir.dk/statistic/register?context=JobApplicationInitiatedCount&feedId=dc2beb84&entryId=85d71bec&page=ShowJob&component=SendApplicationButtonhttps://dispatcher.ofir.dk/statistic/register?context=JobApplicationAppliedCount&feedId=dc2beb84&entryId=85d71bec&page=EmailApplyForm&component=SendApplicationButtonhttps://static.matchwork.com/company/logo/DK/ORS/SoMe/Salg_marketing_og_kommunikation/Marketing/3.jpgIndustrial PhD in Predictive Maintenance12008771Dansk3Læse/ tale938100Product Manager4Marketing363968318noreply@ofir.comDKDanmarkDKDanmarkda-DK