Doctoral student in the area of air transport economics and business @ Université de Technologie de Compiègne, France

Introduction

Year after year, the University of Antwerp has the privilege of welcoming more students. This is no coincidence. Innovative instruction, ground-breaking research and excellent guidance: students and researchers make a conscious choice for these qualities. Each day, our 4 000 employees go to great lengths to realize them. We are constantly in search of colleagues who are ready to invest their efforts with us in our university.

Department

The Faculty of Applied Economics is seeking to fill the following full-time vacancy in the Department of Transport and Regional Economics

Subject area

Doctoral student in the area of air transport economics and business

Job description

The Department of Transport and Regional Economics is looking for reinforcement for its air transport research team. Together with the team, the applicant will conduct cutting-edge research on air transport economics and business.

The applicant will further:

• prepare a doctoral thesis in the field of air transport economics and business;
• contribute to research in the Department of Transport and Regional Economics, in the field of air transport economics and business;
• keep active contact with the air transport industry stakeholders;
• enroll in the university's Ph.D. program;
• write scientific articles about the subject of your research.

Profile and requirements                                                                           

• You hold a master degree in applied economics (or other relevant domains).
• You have relevant knowledge of and genuine interest in transport and preferably air transport economics and business.
• You have a good methodological background. Proven research expertise in quantitative research methods is considered a plus.
• You can submit outstanding academic results.
• Also students in the final year of their degree can apply.
• Your academic qualities comply with the requirements stipulated in the university’s policy.
• You are quality-oriented, conscientious, creative, customer-oriented and cooperative.
• An analytical spirit and a focus on quantification are expected.
• Team player with a sense of initiative and responsibility.
• Excellent verbal and written English communication skills and a willingness to learn Dutch.

We offer

• a contract for a period of one year to start with, with the possibility of renewal for a further period after positive evaluation;
• the start date of the contract is planned for as soon as possible;
• a gross monthly grant ranging from € 2.189,88 - € 2.334,46;
• a dynamic and stimulating work environment with possibilities for extra training in an international context.

How to apply?

• Please send an extended CV and motivation letter to Anne Arekens (anne.arekens@uantwerpen.be). The motivation should on the one hand explain why you are the right candidate for the position and on the other hand indicate what your topic of choice within the domain of air transport would be and how you would approach it. The final topic of the PhD will be determined by the promotor(s) in consultation with the applicant.
• The application deadline is 17 July 2016.
• A pre-selection will be made amongst the submitted applications and the motivation document.
• Selected candidates will be invited for an interview (in person or via Skype).
• The remainder of the selection procedure is specific to the position and will be determined by the selection committee.
• With regard to questions regarding the profile and the description of duties, please contact dr. Wouter Dewulf at wouter.dewulf@uantwerpen.be or +32-3-265 49 36.

The University of Antwerp is a family-friendly organization, with a focus on equal opportunities and diversity. Our HR-policy for researchers was awarded by the European Commission with the quality label 'HR Excellence in research'. 


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PhD Position on Networks & Control @ Université de Technologie de Compiègne, France

Location
=======
PhD Opening at the Heudiasyc Lab, Université de Technologie de Compiègne, France

Description
=========
A PhD position is available at the Heudiasyc Lab of the Technological University of Compiegne, France. The candidate will join the transversal Networking and Control research direction managed by Professors Isabelle Fantoni and Enrico Natalizio.

Duration of Study
============
The position is fully funded for three years and available from September-October 2016.

Educational Requirements/Eligibility 
============================
Graduate students at the M.Sc. or B.Sc. level with background in Electrical and Computer Engineering or Computer Science are encouraged to apply.

*Subject and skills*
================
In the development of distributed networked controlled system of systems, there is a prominent need for supporting networks that can provide high levels of QoS using mobile nodes and off-the-shelf components.  At the same time, the 5G network infrastructure is anticipated to be able to show very high performance using control of dedicated hardware. From this standpoint, the Applicant shall develop a set of control strategies that will be applied to these systems of systems. The devised strategies will ensure the appropriate management and will be oriented to the network performance maximization. In detail, the developed strategies and the associated insights will allow fulfilling specifications and constraints coming from both: (i) the communication point of view (i.e. QoS, interference shaping, etc…) and (ii) the control theory point of view (robustness of the control, system
convergence analysis, task management, etc…).
All the candidate work will converge towards a system that should also include fault tolerance features and be able to show self-* capabilities. The devised control strategy is envisioned to be based on the following strong points:
•    Decentralized network connectivity estimation coupled with agents' mobility control;
•    A two-step strategy for the management of topology control;
•    Combined Power and Mobility Control with system-status based priority assignments.
The first point will render the system capable to drive the network through a specific topology and, at the same time, satisfy communication constraints. The second point revolves around the definition of a general strategy to tackle topology control problems. The third point concerns the design of strategies to switch between mobility and power control approaches dynamically and optimally.

Other background knowledge
======================
Good mathematical background and knowledge in Control Theory and Networking protocols as well as practical skills with programming languages (C/C++) and software tools (e.g., Matlab, NS-2, NS-3) and fluent English (written and spoken) are required. Above all, the applicants must be motivated to learn quickly and work effectively on challenging research problems.

*Application process*
================
The following documents are required:
- CV,
- motivation letter,
- statement of research experience and interests,
- University transcripts
as attachments of an email, whose subject will be "Application for PhD position at the Heudiasyc Lab", which must be addressed to Professors Fantoni and Natalizio (at isabelle.fantoni@hds.utc.fr and enrico.natalizio@hds.utc.fr).
Web links of research articles authored by the applicant are welcome to be included, too.

*Timeline*
==========
- July 15th, 2016: application submission deadline
- July 20th-21th, 2016: interview of the selected candidates
- September-October 2016: position start date

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PhD in Machine Learning, Centrer for Computational Biology, Mines Paris Tech, France

Title:
Detection of epistasis in genome-wide association studies with machine learning methods for therapeutic target identification.

Duration:
36 months

Starting:
03/10/2016

Application deadline: 
13/06/2016

Location:
Paris / Chilly-Mazarin

Laboratory:
Centre for Computational Biology, Mines Paris Tech — Institut Curie — INSERM / In silico biology, Translational Science Unit, Sanofi

Contacts:
* Chloe-Agathe.Azencott@mines-paristech.fr
* Jean-Philippe.Vert@mines-paristech.fr
* Clement.Chatelain@sanofi.com

The Centre for Computational Biology of Mines Paris Tech and the Translational Science Unit of Sanofi are looking for a PhD candidate interested in a joint PhD project between a pharma industry and academic lab to work at the cutting edge of machine learning and genomics in a stimulating interdisciplinary research environment.

The Centre for Computational Biology is a joint laboratory between Mines ParisTech and ARMINES. It is also one of the teams of the U900 joint laboratory between Mines ParisTech, Institut Curie and INSERM dedicated to epidemiology, bioinformatics and systems biology of cancer.

The Translational Sciences Unit has a strategic position in Sanofi to implement translational research approaches throughout the drug value chain to understand the molecular mechanisms responsible for pathologies and to identify targets and biomarkers.

Context:

Genome-wide association studies (GWAS) have generated huge data sets in the past 10 years in order to find association between genetic polymorphisms and phenotypes. Until recently, most GWASs have focused on individual single nucleotide polymorphisms (SNP) markers, effectively looking at the contribution to disease of variants tagged by them in isolation. Thousands of SNPs have been associated with complex diseases by univariate analysis, but in most cases those variants independently explain only a small fraction of the estimated disease heritability (“missing heritability”). Strong evidence indicates today that genetic variants underlying most complex diseases are non-mendelian. These variants are typically not rare in the population. Independently, they show very little effect with low penetrance, but they may interact with each other in complex non-linear ways. This joint behavior of genetic variants is often referred to as epistasis or multilocus interaction. It has been speculated that epistasis ubiquitously contributes to complex diseases, partly because of the sophisticated regulatory mechanisms encoded in the human genome, and thus explains part of the missing heritability .

A vast number of methods for the detection of epistasis have been developed in recent years. However these methods still faces 3 major challenges: 1) statistical methods traditionally used in univariate SNP-phenotype associations are not adequate to find epistasis; 2) the number of combinations to be tested is tremendous, even for pairwise analyses (billions to trillions). This creates statistical power issues, and reaches the limitation of our actual computational capabilities; 3) the interpretation of the analytical results at a biological level is not straightforward.

Objective:

The objective of this PhD thesis will be (i) to develop new approaches for identifying complex multi-locus interactions in GWAS using machine learning methods, such as random forests or deep neural networks, focusing in particular on models stability and results interpretability, (ii) to implement these methods on GPU or in parallel when possible, in order to efficiently process large datasets and to integrate the solutions in the current GWAS analysis pipeline at Sanofi, and (iii) to apply these methods to selected datasets for complex diseases with an important estimated heritability.

Qualifications:

We are looking for a student with strong theoretical and practical knowledge in machine learning, statistics and optimization methods, highly motivated by an interdisciplinary research project that will take place both in an academic and industry environment. The candidate should have good programming skills (Python, R, C) and a strong interest for biology, in particular genetics and systems biology. Experience in Cuda programming or software development is a plus. The position will be open to candidates of any nationality with a master or equivalent degree (computer science, applied mathematics, statistics, data science, bioinformatics or related area). Good communication skills in French and English is required.

The PhD student will be co-supervised by Chloe-Agathe Azencott, Jean-Philippe Vert (Paris / Mines ParisTech) and Clément Chatelain (Chilly-Mazarin / Sanofi) and will be expected to spend time both at Mines and Sanofi laboratories.  During the PhD, the student will be employed by Sanofi, with competitive salary and benefits.

Application/How to Apply

Interested candidates should contact:
* Chloe-Agathe.Azencott@mines-paristech.fr
* Jean-Philippe.Vert@mines-paristech.fr
* Clement.Chatelain@sanofi.com

Applications must contain a curriculum vitae, a publication list (if applicable), a letter of motivation and a list of two contact references.

Interview

• Selected candidates will be interviewed during June 2016.

For more details, 

• please refer to this document (pdf).  

For original information
 http://cbio.ensmp.fr/index.php?wikipage=CbgPositions

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PhD Position (Salary: 1958€/M ) at INRIA Lille, France: Privacy-friendly Distributed Machine Learning

Position

• PhD position: Privacy-friendly distributed machine learning

Introduction/Specification
The Inria Magnet team has an opening for a PhD position on privacy-friendly distributed machine learning. The topic of this Ph.D. project is the development of algorithms to perform tasks which are currently done with complete knowledge of the data in a much more distributed and privacy-friendly way. In particular, the problem of learning a model from the distributed data of many users who do not want to share their data will be considered. The overall goal of this project is to get a better understanding of the potential of private distributed learning, to construct theory supporting this understanding and algorithms exploiting it. Several scenarios will be investigated, depending for instance on whether synchronization between users through a global server is possible. To guarantee privacy, we will study how to adapt methods from secure multi-party computation to statistical machine learning in order to develop efficient algorithms for which one can control the amount of disclosed sensitive information. Where possible, the potential of the obtained results will be demonstrated in real-world applications, such as ride sharing (predicting rides and matching between users without centralization of mobility logs) and crowdsourcing (task recommendation to users without compromising their personal data).

Intake Schedule and Supervisor
The candidate will work under the supervision of Jan Ramon and Aurélien Bellet. The PhD will begin in October 2016. In France, a PhD should be completed at the end of the 3rd year.

Location of the Institute

The working environment is located at the Inria research center in Lille, France. Combining computer sciences with mathematics, Inria’s 3,400 researchers strive to invent the digital technologies of the future. Educated at leading international universities, they creatively integrate basic research with applied research and dedicate themselves to solving real problems, collaborating with the main players in public and private research in France and abroad and transferring the fruits of their work to innovative companies. The researchers at Inria published over 4000 articles a year. They are behind over 270 active patents and 105 start-ups. The 171 project teams are distributed in eight research centers located throughout France. Lille is the capital of the north of France, a metropolis with 1 million inhabitants, with excellent train connection to Brussels (34 min), Paris (1h) and London (1h30), and tons of opportunities for social life.

Eligibility Applicant profile:
- strong background in machine learning, statistics and algorithms
- additional knowledge on distributed distributed systems and cryptography would be appreciated
- some experience in implementation and experimentation is expected
- good writing and speaking English skills

Salary Side information:
Salary: 1958€ the first two years and 2059€ the third year
Salary after taxes: around 1600€ the 1st two years and 1679,76 € the 3rd year (benefits included).
Possibility of French courses.

How to Apply
If interested, send to Jan Ramon jan.ramon@inria.fr (jan [dot] ramon [at] inria [dot] fr) and Aurélien Bellet (aurelien.bellet@inria.fr) as soon as possible: your CV, a statement of interest, and any supporting documents (e.g., recommendation letters) you may consider helpful.

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