Master Thesis Image classification for Turbine inspections using
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hela Sverige Master Thesis Image classification for Turbine inspections using Deep Learning
Are you a master student planning to write your Master Grade during Spring 2021?
Join us on our journey #SiemensEnergy
Siemens Energy's 91,000 employees around the world are passionately pursuing one common goal: to energize society with affordable, reliable, and sustainable energy systems.
Join our great team and put your energy to use."
We are now looking for a student to take on the assignment "Image classification for Turbine inspections using Deep Learning"
The assignment:
As part of our digitalization strategy at Siemens Energy, we are working on automating our fleet inspections operations, in order to reduce costs and increase the hit rate of inspections. In one of the use cases connected to this strategy, we have combined data sets of machines images, and labeled those images according to whether they have faults or not, along with some information about the details of those faults. We also worked on increasing the amount of these data sets, by creating augmented images out of original ones, and labeling the augmented image as well.
Your role in this project is to continue on the process, and use these data sets to build an image classification model, that model is supposed to enable performing inspections automatically out of the new images that we get from the fleet machines.
Your job will also focus on investigating about the business impact of your new proposed solution, and how it is useful for the company in comparison with the current inspection procedures.
Your tasks will be:
* Literature Review of existing methodologies used for image classification for faults detection.
* Explore, process & understand the data available for this MSc thesis project.
* Develop a baseline solution, taking into consideration the applicability of your models on the fleet level.
* Understand and present the business impact of your solution in comparison to company's current inspection processes.
* Validate the methodology for different data sets that represent different machines with different conditions.
Your Profile:
* The project is suitable for a student with academic background in energy systems, engineering, computer science, statistics, mathematics or another relevant field.
* As a student you have strong analytical skills and solid mathematical background.
* Besides, you are interested in data analytics (especially in prescriptive analytics) and you must have programming skills (preferable: Python, R or Julia).
* We consider meritorious skills the knowledge of machine learning/deep learning-oriented libraries (scikit-learn, caret, mlr, keras, tensorflow, pytorch etc...), data handling libraries (Pandas or tidyverse).
* We consider meritorious a GitHub record with deep learning projects.
* We consider meritorious Open-Source contributions.
Why should you be working at Siemens?
Siemens Energy is one of the world's leading energy technology companies. The company works with its customers and partners on energy systems for the future, thus supporting the transition to a more sustainable world. With its portfolio of products, solutions and services, Siemens Energy covers almost the entire energy value chain - from power generation and transmission to storage. The portfolio includes conventional and renewable energy technology, such as gas and steam turbines, hybrid power plants operated with hydrogen, and power generators and transformers. More than 50 percent of the portfolio has already been decarbonized. A majority stake in the listed company Siemens Gamesa Renewable Energy (SGRE) makes Siemens Energy a global market leader for renewable energies. An estimated one-sixth of the electricity generated worldwide is based on technologies from Siemens Energy. Siemens Energy employs 91,000 people worldwide in more than 90 countries and generated revenue of around EUR29 billion in fiscal year 2019. In Sweden Siemens Energy has 2600 employees in 10 locations.
At Siemens we value diversity by inclusion and by cooperating with people with different mindset, background, experience, competence and personal traits - in all organisational levels.
Read more about Siemens here:
www.siemens-energy.com.Application
Do not hesitate - apply today via
https://jobs.siemens-energy.com/jobs, refnr 221356 and no later than November 6^th.
For questions about the role please contact recruiting manager Ronny Norberg on +46 (122) 82304.
For questions about the technicalities of the projects please contact
edgar.bahilo_rodriguez@siemens.com or
mohamed-ahmed@siemens.comPlace of work: Finspång
Place of work: Finspång
Trade Union representatives:
Veronica Andersson, Unionen, 0122-840 21
Simon Von Eckardstein, Sveriges Ingenjörer, 0122-842 24
Jan Lundgren, Ledarna, 0122-812 33
Jonny Persson, IF Metall, 0122-817 69
Varaktighet, arbetstid
PARTTIME CONTRACT
Publiceringsdatum2020-10-14ErsättningSALARY
Så ansöker duSista dag att ansöka är 2020-11-06
Klicka på denna länk för att göra din ansökanFöretagSiemens Energy AB
Arbetsgivarens referens Arbetsgivarens referens för detta jobb är "221356".
Omfattning Detta är ett deltidsjobb.
Arbetsgivare Siemens Energy AB (org.nr 556606-6048)
Arbetsplats Siemens Energy
Jobbnummer 5399222
Observera att sista ansökningsdag har passerat.