Vacancies and Job Openings

 

Phd candidate – Smart marine operation and maintenance of ships (Open)

PhD position – Smarter operation and maintenance of ships, using simulator-based condition predictions for decision support – applications on remote and autonomous operations.

The Department of Ocean Operations and Civil Engineering, has a vacancy of one PhD position which runs over 3 years (or 4 years including 25 % teaching). The position is funded by Markom2020 and is part of the joint PhD program in Nautical Operations. This is a research position that will lead to the doctoral degree (PhD) in addition to contributing to professional development at the faculty. The workplace is at NTNU in Ålesund, but the candidate will also participate and collaborate with a team of PhD students in Ålesund and at the Department of Marine Technology located at NTNU in Trondheim.
Description of the PhD research project

A number of research projects are investigating the feasibility of unmanned (or reduced crew) vessel concepts. The task of such projects is a real challenge, since marine vessels consists of complex machinery systems that require continuous control, periodic maintenance and in case of emergency – on-site repair interventions. All these actions are currently done by on board technicians, but the work required can be potentially minimized by the application of advanced control systems coupled with artificial intelligence systems that will predict condition and possible future failures, and hereby advise to operators to schedule interventions necessary to minimize the costs and down-time.

However, there is a number of challenges related to implementation of such systems. First of all, it should be mentioned that modern ships are “packed” with advanced technical solutions which in their turn require precise monitoring and control, hence thousands of different sensors and transducers are installed onboard. These sensors provide the crew with information about the current status of various processes/systems and “help” to make the right decisions. Most of this information is also stored on a digital drive and can be effectively used in predictive analytics, but ship-owners simply do not know how to utilize it.

The main aim of the proposed study is to develop and test methods for robust condition-based on-board decision support systems for operation and maintenance of machinery systems. Main power systems are complex and integrated systems, so as a first step a certain subsystem(s) as for should be chosen. The raw data might be of large volumes and variable quality, so the appropriate data reduction approaches should be identified and implemented. This will allow to reduce data volume and at the same time increase its value for analysis.

The next step is to study the available condition based maintenance techniques which in general can be divided into 3 groups: model driven, data driven and knowledge driven approach. After the reasoning for the chosen technique the model should be built for the considered system. The final step is to validate the applicability of the model to the real process.

Qualifications

The position requires a Master’s degree in engineering science within the major fields: mechanical engineering, cybernetics, maritime technology or similar. The preferred candidate has a solid knowledge and interest in modelling and simulation of energy systems, and/or cybernetics and sensor technology. The candidate should be enthusiastic and highly motivated and be willing to work both independently and with other researchers.

The candidate must also fulfil the requirement for admission to a doctoral program

  • The applicants must hold a Master’s Degree as mentioned above, with an average grade B or better measured in ECTS (European Credit Transfer System) grades, or similar education at the equivalent level
  • Good theoretical and analytical skills
  • Ability to work independently as well as in team
  • Potential for research at an international level and keen interest in the wider own research. Ability to engage in cross-diciplinary teams
  • Written and oral fluency in English. The following tests can be used as such documentation: TOEFL, IELTS or Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). Minimum scores are:

TOEFL: 600 (paper-based test) 92 (Internet-based test)

IELTS: 6,5 with no section lower than 5.5 (only Academic IELTS test accepted)

CAE/CPE: Grade B or A

In extraordinary circumstances, formal documentation of language skills can be relinquished. In such cases the candidate’s language skills will be assessed in a personal interview.

Conditions

PhD Candidates are remunerated in the State’s salary system, code 1017, starting at wage level 50, at a minimum of NOK 432 700 per year be before tax. There will be a 2 % deduction to the Norwegian Public Service Pension Fund from gross wage.

Engagement as a PhD Candidate is done in accordance with “Regulation concerning terms and conditions of employment for the posts of post-doctoral research fellow, research fellow, research assistant and resident”, given by the Ministry of Education and Research of 19.07.2010.

The goal of the positions is to obtain a PhD degree. Applicants will engage in an organized PhD training program, and appointment requires approval of the applicants plan for a PhD study within three months from the date of commencement.

See http://www.ntnu.edu/ivt/phd  for more information.

The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants. The positions adhere to the Norwegian Government’s policy of balanced ethnicity, age and gender. Women are encouraged to apply.

According to the new Freedom of Information Act, information concerning the applicant may be made public even if the applicant has requested not to be included in the list of applicants.

The application must contain information of educational background and work experience. Certified copies of transcripts and reference letters should be enclosed. Applications with CV, grade transcripts and other enclosures should to be submitted electronically via this page.

Application deadline is 31.01.2017. Start-up date may be discussed, but tentatively August 2017.

For further information about the position, please contact: Prof. Vilmar Æsøy ( vilmar.aesoy@ntnu.no), Prof. Sergey Ushakov (sergey.ushakov@ntnu.no) and Prof. Houxiang Zhang (hozh@ntnu.no)

Apply for the position, please visit the official following webpage or visit NTNU.no.

https://www.jobbnorge.no/ledige-stillinger/stilling/132124/phd-position-smarter-operation-and-maintenance-of-ships

 

Phd candidate – Data-based Ship Motion Prediction in Offshore Operations (Closed)

 

The Mechatronics lab at Faculty of Marine Technology and Operations has vacant one PhD position which runs over 4 years including 25 % teaching. This is a resarch position that will lead ut to the doctoral degree (PhD) in addition to contributing to professional development at the faculty. The workplace is at NTNU in Ålesund, but the candidate will also participate in an organized doctoral degree program at NTNU in Trondheim. The candidate will, together with the academic research group at the college and research teams in the collaborative companies, develop knowledge within the specified area of resarch; data-based ship motion prediction in offshore operations.

Description of the PhD study

With the growth of emerging demands from offshore applications, such as seabed survey, pipeline maintenance and offshore oil installations, the complexity of ship maeuvering during offshore operations, increases as more constraints from position accuracy, limited working space, and collision avoidance between vessels and floating structures, need to be taken into consideration. To assist to address the complexity and guarantee the performance, new knowledge and technology for such constrained ship maneuvering, are urgently demanded.

Ship motion prediction is of great importance. The ship dynamic varies with navigational status such as the load and the speed, and perturbations orginated from the operation environment including waves, wind and currents are complex and unpredictable. It is difficult to predict the ship motion without fully dynamic model.

Data based predicition in this case can address the difficulty of obtaining precise dynamic model. On the one hand, huge amount of sensor data can be gathered from different sources of the shiå in various maneuvering scenarios. On the other hand, analysing and modelling of these sensor data by using artificial intelligent methods such as neural network and extended Kalman filter, can be achieved for prediction purpose, which consequently can provide valid suggestions and assist the pilot to increase maneuvering ability.

This PhD will focus on data-based prediction in the offshore operations. Data can be obtained either from real or simulated vessels. Furthermore, weather data should be taken into consideration, from a practical perspective, to enhance the prediction precision and provide the pilot with valid suggestions.

Qualifications

  • MSc in automation, or computer science, with an average grad B or better measured in ECTS (European Credit Tranfer System) grades, or an education at the equivalent level
  • Good programming skills
  • Good theoretical and analytical skills
  • Ability to work independently as well as in team
  • Potential for research at an international level and keen interest in the wider own research. Ability to engage in cross-diciplinary teams

Written and oral fluency in English. The following tests can be used as such documentation: TOEFL, IELTS or Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). Minimum scores are:

  • TOEFL: 600 (paper-based test) 92 (Internet-based test)
  • IELTS: 6,5 with no section lower than 5.5 (only Academic IELTS test accepted)
  • CAE/CPE: Grade B or A

In extraordinary circumstances, formal documentation of language skills can be relinquished. In such cases the candidate’s language skills will be assessed in a personal interview.

Extra requirements

  • Good at signal processing
  • Have knowledge in artificial intelligense, especially the experience related to prediction

Conditions

It is essential that the succesful candidate filles the requriement for admission to a doctoral program. The PhD candidate must work at NTNU in Ålesund and participate in an organized doctoral study. The sucessful candidate will be part of a creative and informal academic environment that places heavy demands on independence, ability to take initiative and to cooperate.

PhD candidates are remunerated in code 1017, starting at wage level 50, currently gross NOK 430 200 before tax. There will be a 2 % deduction to the Norwegian Public Service Pension Fund from the gross wage.

The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants. The position adheres to the Norwegian Government’s policy of balanced ethnicity, age and gender. There are few womein in the faculty and women are encouraged to apply. According to the new Freedom of Information Act, information concerning the applicant may be made public even if the applicant has requested not to be included in the list of applicants.

A CV with full deatils of tranining and practice must be included in the online application, together with certified copies of diplomas and certificates.Applicants will be invited for interviews in which original diplomas/certificates etc. are expected to be presented

Supervisors: Prof. Houxiang Zhang, Prof. Thor I. Fossen, and Dr. Bjørnar Vik (Rolls-Royce Marine)

More information about the position can be obtained from Prof. Houxiang Zhang, hozh@ntnu.no.

Apply for the position, please visit the official following webpage or visit NTNU.no.

https://www.jobbnorge.no/ledige-stillinger/stilling/126517/phd-candidate-data-based-ship-motion-prediction-in-offshore-operations?p=1&reset=1

 

 

 

PhD Candidate – A Cross-modal Integrated Sensor Fusion System for Fatigue and Awareness Assessment in Demanding Marine Operations (Closed)

The Mechatronics lab at Faculty of Marine Technology and Operations has vacant one PhD position which runs over 3 years (or 4 years including 25 % teaching). The position is funded by SFI Mechatronics. This is a resarch position that will lead ut to the doctoral degree (PhD) in addition to contributing to professional development at the faculty. The workplace is at NTNU in Ålesund, but the candidate will also participate in an organized doctoral degree program at NTNU in Trondheim. The candidate will, together with the academic research group at the college and research teams in the collaborative companies, develop knowledge within the specified area of resarch.

SFI Offshore Mechatronics

The research center SFI Offshore Mechatronics officially commenced on April 1, 2015. The vision for the SFI is to become the international knowledge and research hub for the next generation of advanced offshore mechatronic systems for autonomous operation and condition monitoring of topside drilling system under the control of land-based operation centers, to ensure safe and efficient operation in deeper water and in harsh environments.

Description of the PhD study

Marine operations are becoming more and more demanding. The complexity increases even further taking into account that these operations require a much greater coordination between professionals during e.g. ship maneuvering and crane, winch and ROV operations, often in coordinated operations with a rig and other ships.

Currently a number of studies conducted by various maritime organizations reported that more than 75 % of accidents of ships worldvide are due to human and organizational errors. As a result, it is a matter of prority to look into the human element in order to ensure safety and efficiency during marine operations. Mitigating risk due to the human element is of vital importance.

There is an urgent need to develop methods and tools that will help us understand human operator’s working situation with greater accuracy and therefore a more reliable modelling and simulation of risk assessment during a demanding marine operation.This is the most important knowledge that needs to be dentified in this PhD study. Multiple sensors are preferred for monitoring different body parts of the operator, from where fatigue or loss of concentration can easily manifest. Furthermore, multi-sensor fusion, as the core of this study, will be used to increase the quality and the usefulness of sensor data, generating more accurate and complete model description for marine operation performance assessment. Note that the system is application oriented. Therefore, the system should be expandable according to demands.

For this PhD study, it will mainly focus on applications for marine operations, including

  • Real-time behaviour monitoring
  • Fatigue/risk assessment
  • Behaviour analysis

Qualifications

  • The applicants must own a MSc in automation, or computer science, with an average grad B or better measured in ECTS (European Credit Tranfer System) grades, or an education at the equivalent level
  • Good programming skills
  • Good theoretical and analytical skills
  • Ability to work independently as well as in team
  • Keen interest in the wider context of own research and ability to engage in cross-diciplinary teams

Written and oral fluency in English. The following tests can be used as such documentation: TOEFL, IELTS or Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). Minimum scores are:

  • TOEFL: 600 (paper-based test) 92 (Internet-based test)
  • IELTS: 6,5 with no section lower than 5.5 (only Academic IELTS test accepted)
  • CAE/CPE: Grade B or A

In extraordinary circumstances, formal documentation of language skills can be relinquished. In such cases the candidate’s language skills will be assessed in a personal interview.

Extra requirements:

  • Know the hardware, peripherals and sensors
  • Have knowledge in artificial intelligense, especially the experience related to sensor fusion

Conditions

It is essential that the succesful candidate fills the requriement for admission to a doctoral program. The PhD candidate must work at NTNU in Ålesund and participate in an organized doctoral study. The sucessful candidate will be part of a creative and informal academic environment that places heavy demands on independence, ability to take initiative and to cooperate.

PhD candidates are remunerated in code 1017, starting at wage level 50, currently gross NOK 430 200 before tax. There will be a 2 % deduction to the Norwegian Public Service Pension Fund from the gross wage.

The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants. The position adheres to the Norwegian Government’s policy of balanced ethnicity, age and gender. There are few womein in the faculty and women are encouraged to apply. According to the new Freedom of Information Act, information concerning the applicant may be made public even if the applicant has requested not to be included in the list of applicants.

A CV with full details of tranining and practice must be included in the online application, together with certified copies of diplomas and certificates. Applicants will be invited for interviews in which original diplomas/certificates etc. are expected to be presented

More information about the position can be obtained from Prof. Houxiang Zhang, hozh@ntnu.no.

In order to apply for the position, please visit the following link.

https://www.jobbnorge.no/ledige-stillinger/stilling/126567/phd-candidate-a-cross-modal-integrated-sensor-fusion-system-for-fatigue-and-awareness-asessment-in-demanding-marine-operations

 

Soon new Ph.D positions will be open.

 

 

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