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TUBITAK Post-Doctoral Research Fellow

About Sabancı University

Established by Sabancı Foundation in 1994, Sabancı University provides a world class education to its students from undergraduate to doctorate levels. It is distinguished by its educational system which was unique in Turkey when Sabancı University started its educational activities in 1999. It offers freedom to all its students to choose their academic program within the first two years after they are enrolled in the university. Sabancı University has been the most entrepreneurial and innovative foundation university in the University Entrepreneurship and Innovation Index produced by the Ministry of Science, Industry and Technology of Turkey since 2012. It also ranks first among the universities from Turkey in the Times Higher Education World University Rankings 2020. As a young university with twenty years of history, Sabancı University aspires to become an international reference point for innovation in education and research.

Overview

Sabancı University Integrated Manufacturing Research and Application Center (SU IMC) invites applications for a postdoctoral fellowship to support the TUBITAK-funded project Development and Experimental Verification of Numerical Method Based Topology Optimization Algorithms for Additive Manufacturing. 

SU IMC is the industrial scale research and technology development center that provides laboratory test, prototype manufacturing, design and simulation services, composite materials in the scope of research and development services, and design, manufacturing, assembly and process prototyping services in the area of manufacturing technologies, also, provides consultancy and training services to governmental organizations and industry corporations.

Unlike conventional manufacturing processes, additive manufacturing provides the manufacturing of complex parts directly from computer-aided design models in almost net-shape form without any waste material in a short time without using any molds or tools. Therefore, it is very important to develop novel additive manufacturing methods to ensure manufacturing of these critical parts with less-weight while satisfying the needed requirements. This project assesses and develops novel topology-optimization algorithms and methods, which takes the residual stresses, caused plastic deformation and possible cracks into account, for additively manufacturing of critical and high-performance parts used in aerospace applications, and test the manufactured parts under the necessary environmental conditions.

Responsibilities

The Post-doctoral Fellow is expected to support members of the research team in developing topology optimization methods, analysing data using in-house codes, and transform these analyses into research papers and academic publications. He/she will also be in charge as research manager, supporting the SU Faculty Members, Professor Adnan Kefal and Professor Bahattin Koc, in coordinating all research activities. The fellow will have also the opportunity to develop personal research leveraging the project’s data.

Qualifications

  • PhD degree in Mechanical, Aerospace, Manufacturing Engineering or other Engineering Sciences, 
  • Expertise in computational mechanics, modelling, topology optimization, finite element coding, peridynamics, additive manufacturing, 
  • A proven track record of publication, 
  • Fluent speaking and excellent writing skills in English, 
  • Good team-work and communication skills.

How to Apply

The deadline for applications is November 1st, 2020. Qualified candidates are asked to provide Curriculum Vitae, including a list of publications, a Motivation Letter and a Post-doctoral Research Project Abstract. 

Applicants are requested to complete an online application form at http://sucrm.sabanciuniv.edu/academiccv/application.php 

The position is to start ASAP. 

Sabancı University is committed to the principle of equal opportunity and equal treatment in education and employment. The University respects all individuals without any discrimination of gender, religion, national and ethnic origin, race, color, physical disability, physical appearance, marital or parental status, sexual orientation, age, or political affiliation in the administration of its educational, admission and employment policies, and its scholarship and university-sponsored programs.