A postdoc and a PhD studentship in compressive sensing in related fields.

Two announcements, one of which is on the Compressive Sensing jobs page:

Matthieu Puigt sent me the following:

Dear Igor,

there is a post-doc position opening in our group, in the field of audio signal processing. Even if the position is not limited to these topics, the group is particularly interested in compressed sensing, sparse representations/approximations, matrix completion, and matrix factorization. As many researchers in these fields follow your blog, would you accept to forward the following advertisement on Nuit Blanche?

Thanks in advance.

Regards,

Matthieu

Here is the announcement:

We have a new opening for a postdoctoral researcher on audio signal processing. At FORTH-ICS, located at Crete, Greece. Some details for the position follow. This info is also available at the following link:

http://www.ics.forth.gr/~mouchtar/job_openings.html

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Project: AVID-MODE: FP7-PEOPLE-IAPP EU-funded project at FORTH-ICS

Position: Post-doctoral researcher

Start date: Immediately

Duration: 12-18 months

Salary: 39.000-42.000 EUR/year (gross income depending on family status)

Description:

The Telecommunications and Networks Laboratory (TNL) of the Institute of Computer Science (ICS) at the Foundation for Research and Technology-Hellas (FORTH), is seeking recent PhD graduates for a post-doctoral position in the field of Audio Signal Processing. The successful candidate will have the opportunity to work on one or more of several interesting projects including multichannel audio and surround sound, teleconferencing and noise cancellation, sound source separation/beamforming, and audio codec design and implementation.

The successful candidate will be offered the opportunity to:

• Have access to laboratory space and significant resources, and interact with researchers from other FORTH-ICS labs.
• Work within a team with a strong international flavour including many researchers of non-Greek origin.
• Collaborate with academic and industrial partners in Greece and abroad.
• Work on a research subject which best fits his/her background and future goals, within the general areas described above.

Required skills:

• A PhD in computer science, electrical engineering, or related field.
• Substantial research experience in signal processing for audio signals, as evidenced by a good publication record.
• Significant programming experience in Matlab and/or C/C++.

Eligibility:

• Recent PhD graduates (less than 10 years after obtaining their BS degree).
• Non-Greek nationals, who have not resided in Greece more than 12 months in the 3 years prior to the appointment.
• Greek nationals who have resided and held their primary activities outside Greece for at least 3 of the last 4 years.
• FORTH is an equal opportunity employer; female candidates are particularly encouraged to apply.

To apply, please send a cover letter and a CV to Prof. Mouchtaris.

e-mail:mouchtar@ics.forth.gr

http:// www.ics.forth.gr/~mouchtar

Lenka Zdeborova  has a suggestion for PhD studentship at CEA (see how to obtain funding here)

Physique statistique de l'acquisition comprimée // Statistical physics of compressed sensing

Thèse proposée par (PhD thesis proposed by) Lenka ZDEBOROVA

Compressed sensing is a method triggering a major revolution in signal acquisition. It consists in sampling a sparse signal at low rate and later using computational power for its exact reconstruction, so that only the necessary information is measured. Examples of direct applications include speeding up magnetic resonance imaging without the loss of resolution, or sensing and compressing data simultaneously thus saving memory and acquisition time. Methods of statistical physics of disordered systems (such as the replica method, cavity method and related message passing algorithms) provide a very useful tool to study compressed sensing and to design more efficient measurement protocols. The subject of this thesis is to explore this direction further. The work will include theoretical computations and analysis of the phase diagram and related algorithms, as well as development of new algorithms, and application to real data from MRI, computed tomography etc.

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