Job offer – we are recruiting two Ph.D. candidates supported by the EU-H2020-MSCA-ITN project TraDE-OPT, specifically for ESR 9 and 10, to work on Optimization Methods for Big Data, Machine Learning or Network Systems.
2 PhD positions available at University Politehnica Bucharest
We are recruiting 2 PhD candidates supported by EU-H2020-MSCA-ITN project TraDE-OPT (https://trade-opt-itn.eu), specifically for ESR 9 and 10, to work on Optimization Methods for Big Data, Machine Learning or Network Systems.
PhD 1: Scalable optimization algorithms for huge-scale optimization problems In this project (ESR 9) new algorithms will be designed and their computational performance assessed for huge-scale optimization problems, based on the structure present in the problem, such as data structure or structure in the objective function and based on different models of computations, such as parallel or distributed computing. To obtain scalable algorithms, stochastic framework will be combined with fast optimization schemes such as higher-order methods. Applications in machine learning field are expected. The student will also visit Universite Catholique de Louvain (Belgium) and Supelec (France) for 3 months. He/she will also have an internship at the company CAMELOT (Italy) for 3 months to work on a real application related to unsupervised feature selection.
Phd 2: Significant advances in the state of the art of decision-making for complex network systems.
In this project (ESR 10) new efficient control schemes for large-scale network systems will be developed. In order to be able to control large scale networks we first investigate optimization-based model reduction techniques using clustering for obtaining accurate models of reasonable dimension for networks. Then, we will use these models to derive optimization-based control schemes, such as model predictive control, to improve the decision making in network systems. Application to real world challenges is expected, such as power or biological systems. The student will also visit UNIGE (Italy) and Universite Catholique de Louvain (Belgium) for 3 months. He/she will also have an internship at the company N-Side (Belgium) for 3 months to work on scalable control solutions for data-driven problems in power networks.
Requirements:
We are looking for candidates with strong mathematical and computations skills (optimization, linear algebra, control, matlab/python) to work on theoretical and algorithmic projects at the interface between optimization, machine learning and control. The positions are for 3 years and they are available immediately (before August 2020). Interested candidates are invited to send:
- Half-page cover letter motivating your interest and suitability for the position
- Detailed curriculum vitae including research experience and any previous publications
- Transcripts of academic records indicating courses taken (including grades); please indicate also the optimization courses you attend and a short description.
- Half-page summary of your MSc thesis
- Contact details of two relevant references (email, phone number)
by email at the email address: ion.necoara@acse.pub.ro.
Eligibility criteria:
Candidates must –at the date of recruitment (September 2020)– (i) have obtained the MSc degree entitling you to embark on a doctorate; (ii) be within the first four years of your research career (i.e. after finishing master) and not have a doctoral degree; (iii) candidates must not have resided or carried out your main activity (work, studies, etc.) in Romania for more than 12 months in the 3 years immediately prior to the recruitment date.
Conditions of employment:
The PhD students will work in the group of Professor Ion Necoara (https://acse.pub.ro/person/ion-necoara/), that belongs to the Automatic Control and Systems Engineering Department, University Politehnica Bucharest, Romania. These are full positions and the salary will be according to European Commission funding rate (gross salary between 2.500 and 3.000 euro). You can get more information about salary and ITNs in Information Note for ITN Fellows.
For more information about the project, please contact Prof. Ion Necoara (ion.necoara@acse.pub.ro).
