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PhD position in MSCA-ITN project FibreNet in the field of automated microrobotic characterization of fibres and fibre bond strenghts

FibreNet is a Marie Skłodowska-Curie European Training Network (ETN) within Horizon 2020 EU programme. It forms an umbrella-project that combines the individual research projects of the 15 hired PhD candidates and offers common fibre-related training.

FibreNet consortium consists of seven European universities and eight European companies who will each hire 1-3 PhD students or host 1-3 months long internships (called secondments) as part of the training program. You will be recruited by one organization for the whole period of three years, i.e., also during the secondments. The host organization is determined by the research project for which you have applied.

Fibres have a central role in determining the key characteristics of many everyday products. A good example is the role of cellulose fibres in determining the strength of cardboard. The main objective of FibreNet is to develop a set of new tools and methods to control the properties of different products that contain bio-fibres as their functional parts (bio-fibres as opposed to man-made fibres, such as carbon fibre). The developed methods will apply over a range of different fibre-related applications.

We will focus on growing sectors of bio-based fibre products including packaging, bio-composites, specialty textiles, and medical products.

Thus, the higher-level objectives of FibreNet can be summarized as:

• to boost the competitiveness of biocomposites in the composites sector and to improve the strength and durability properties of composites by enhancing the fibre-matrix interface properties,

• to improve the price-competitiveness and functionality of paper and fibre-based packages by developing new modification, characterization and modelling methods and tools,

• to improve biocompatibility, to extend the linear drug release period and increase pilot production capabilities in fibre-based wound healing and tissue engineering applications.

In order to achieve the objectives, each individual research project will tackle different bio-fibre related problems related to functionalization, characterization, modelling and/or to production. The scale of operation will span from nanoscale via microscale to product scale.

Job description:

This PhD research project contributes to the FibreNet objectives by developing automated microrobotic methods for characterization of fibre and fibre bond strengths.

The mechanical properties of fibres and fibre-fibre bonds play a significant role in the mechanical properties of products based on fibre networks, such as board and paper. The current characterization methods are tedious and slow. TUT has developed methods for microrobotic fibre characterization with a present yield of approximately 10 samples/day.

The aim of this PhD project is to improve the measurement throughput of bio-based fibres and their bonds to a level required in industrial R&D projects by combining machine learning methods with microrobotics. The thesis work will be at the forefront of microrobotics research as it one of the first studies combining machine learning and microrobotics. In addition to the field of microrobotics, the thesis work will give an impact to field of fibre science and the R&D in the related industry paper, board paper chemicals.

Results: The project is expected to develop methods for automating microrobotic fibre and bond measurement. The work will start with fibre measurements and will be extended to bond measurements during the project. The expected results are as follows:

  1. Microrobotic system which can autonomously measure fibre and/or bond strengths, and provide multi-mode data to better understand the measurement process, and sample and material properties.
  2. Improvement of the situation awareness capabilities of microrobotic systems performing microscale material testing.
  3. Implementation of a supervisory system to operate the manipulators and grippers
Requirements:

The general requirements for all FibreNet positions apply here, i.e.:

• you may already be in a PhD program but you cannot be a PhD holder,

• you must have less than 4 years of research experience, i.e., you should be an early-stage researcher,

• you must not have resided or carried out your main activity in the country of the hiring organization for more than 12 months during the last 3 years immediately prior to the recruitment (short stays such as holidays and/or compulsory national service are not taken into account), and

• you should have a high-level knowledge of the English language.

Furthermore, the position-related requirements are:

• Master’s degree (completed at latest in July 2018) in robotics, mechatronics, or other comparable Master’s degree,

• Knowledge of software engineering and basics of machine learning methods is beneficial,

• Enrollment as a doctoral student at TUT within four months after signing the contract,

• Ability to work independently as a member of TUT research team and of the FibreNet community

Salary:

Gross salary, before mandatory employer deductions (22%) AND income tax:

€4226.26 (for those without family)

€4726.26 (for those with family or children at the time of the recruitment)

The family status will be determined at the date of the (first) recruitment. For more details, see Section 5 of the MSCA-ITN guide. TUT offers a range of staff benefits e.g., occupational health care, flexible working hours, excellent campus sport facilities, and restaurants and cafés on campus with staff discounts.

Finland has one of the most advanced and comprehensive welfare systems in the world. It includes sickness, maternity, paternity and various family benefits, such as child-care services, and a comprehensive healthcare system. For more details, check the EU Comission’s document on social security rights in Finland

Trial period:

The appointment is subject to the satisfactory completion of a trial period of four (4) months.

Other:

The position will be filled now for a fixed-term period of 36 months. Appointment is expected to commence on June 2018 or as mutually agreed (1-2 months changes to the intended starting time are possible).

For more information, please contact:

• Supervisor Professor Pasi Kallio, pasi.kallio@tut.fi (on scientific content)

• HR Specialist Päivi Peltonen, paivi.peltonen@tut.fi (on application procedure)

Fibrenet web pages (consortium's job posting, our vacancy number is IRP2)

TUT Foundation – Tampere University of Technology (TUT), Tampere, Finland

How to apply:

Applications must be submitted in English by TUT online application form. The closing date for applications is Mearch 11th 2018 (24.00 EET / 22.00 UTC).

Mandatory appendices:

• a Curriculum Vitae,

• a letter of motivation (maximum of one page),

• the contact details of two referees,

• a copy of B.Sc. and M.Sc. certificates with annexes, and

• a language certificate (IELTS, TOEFL, PTE Academic, Cambridge Language Certificate (Proficiency CPE or Advanced CAE) if available.

In case no suitable candidates are found, Tampere University of Technology reserves the right to re-open the call.

Additional information on attachments to applications.

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