Open PhD positions

Announcement: 15 PhD positions fully funded for 3 years within A-WEAR Joint Doctorate Network

Target audience: fresh MSc graduates in various engineering fields (who have completed their first master no earlier than Fall 2015 or who will soon complete their MSc) and who are passionate about pursuing a PhD in a research field of high relevance to today’s society (wearable computing & IoT).

Job description: fully funded 36 months PhD positions towards double/joint PhD programs in 5 top European technical universities in Finland, Italy, Spain, Czech republic, and Romania
Gross salary (approx. in EUR/month): 3600 (FI), 2800 (ES), 2000 (RO), 2400 (CZ), 2900 (IT)
Application deadline: 28th of February 2019

Starting time of the PhD: Fall 2019

Selection criteria: Study records Bsc + Msc (20%); Work & research experience (15%); Motivation (20%); Clarity, relevance, innovativeness, and technical soundness of the ’Dissertation Essay’ (25%); Letters of recommendation (10%); Positive attitude, previous mobility experience, good communication skills (10%); English proficiency: fail/pass criterion.

We strive to improve the gender balance in our research groups and encourage female candidates to apply. At the end of the evaluation process, the recruitment committee will decide which candidates to select for each project, taking into account the candidates’ preferences and potential. In case of equal qualifications between a male and a female candidate for the final position, the balance at network level may affect the decision.

More information and link to the application page: www.a-wear.eu/recruitment or https://euraxess.ec.europa.eu/jobs/364125

Machine learning in software development

The subject of the article is the “coding style” concept and the main approaches to detecting the individual style of a programmer. The entire process of creating a software product from this point of view and the main features of programming style are analyzed. It emphasizes the relevance and commercial significance of the problem in terms of product support, plagiarism, work of a large developer’s community in a single repository, an evolution of developer skills. Computational stylometry issues, a possibility of using programming paradigms as an additional factor of style identification are considered. It offers the idea of creating a software tool that allows to identify the style of the author who wrote a particular program fragment and allows less experienced developers to follow the rules accepted in the major part of the repository and determined by coding style of "experts", which leads the code to a uniform format that is easier to maintain and make adjustments. Globally, this stage of analyzing the original (and then the modified code) allows improving the existing algorithms for automatic synthesis of programs.

Our new paper: Using Machine Learning Methods to Establish Program Authorship