<div dir="ltr"><br clear="all"><div><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div><div dir="ltr"> <br>Yours<br><br>Arne<br><i><br></i>-----------------------------------------<br> Arne Elofsson Science for Life Laboratory<br> Tel:+46-(0)70 695 1045 Stockholm University<br> <a href="http://bioinfo.se/" target="_blank">http://bioinfo.se/</a> Box 1031, <br> Email: <a href="mailto:arne@bioinfo.se" target="_blank">arne@bioinfo.se</a> 17121 Solna, Sweden<br> Twitter: <a href="https://twitter.com/arneelof" target="_blank">https://twitter.com/arneelof</a><br> Scholar: <a href="http://scholar.google.se/citations?user=s3OCM3AAAAAJ" target="_blank">http://scholar.google.se/citations?user=s3OCM3AAAAAJ</a><br> ORCID: 0000-0002-7115-9751</div></div></div></div></div><br><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">---------- Forwarded message ---------<br>From: <b class="gmail_sendername" dir="auto">Simona Cocco</b> <span dir="auto"><<a href="mailto:simona.cocco@phys.ens.fr">simona.cocco@phys.ens.fr</a>></span><br>Date: Tue, Dec 29, 2020 at 5:13 PM<br>Subject: Post-doc position on Inference of RNA structure and function from sequence data at ENS<br>To: Remi Monasson <<a href="mailto:remi.monasson@phys.ens.fr">remi.monasson@phys.ens.fr</a>><br></div><br><br>
<div>
<p>Dear colleagues,<br>
</p>
<div>
<div dir="ltr" style="color:rgb(34,34,34);font-family:Arial,Helvetica,sans-serif"><font face="arial, sans-serif">I am writing to advertise a
post-doctoral opening on statistical physics and inference
for biological data.</font></div>
<div dir="ltr" style="color:rgb(34,34,34);font-family:Arial,Helvetica,sans-serif"><font face="arial, sans-serif">Please forward this announcement to
potential candidates. <br>
</font></div>
<div dir="ltr" style="color:rgb(34,34,34);font-family:Arial,Helvetica,sans-serif"><font face="arial, sans-serif"><br>
</font></div>
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<div><font face="arial, sans-serif">Best wishes,</font></div>
<div><font face="arial, sans-serif">Simona Cocco<br>
</font></div>
<div><font face="arial, sans-serif"><br>
</font></div>
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<p class="MsoNormal"><b><span>Postdoc position on </span></b></p>
<p class="MsoNormal"><b><span>Inference
of RNA
structure and function from sequence data </span></b></p>
<p class="MsoNormal"><span> </span></p>
<p class="MsoNormal"><span>Laboratory of Physics of the Ecole Normale Supérieure, <br>
</span></p>
<p class="MsoNormal"><span>under
the supervision of</span><span> Simona Cocco and Rémi Monasson</span><span></span><br>
</p>
<span></span>
<p class="MsoNormal"><span>
<br>
</span></p>
<p class="MsoNormal"><span><br>
<b><span style="background:white">Context and project:</span></b><br>
<span style="background:white"> RNA, long recognized as a
crucial intermediate
in the fundamental </span> <span style="background:white">biological
process of production of proteins from genetic
material (DNA) is also
involved in many catalytic and enzymatic processes.</span></span></p>
<p class="MsoNormal"><span><span style="background:white"> In this context, a
fundamental question is to relate the sequence of RNA
molecule to its structural
and functional properties. The sequence </span><span style="background:white">content must encode the 3D
conformation of RNA
(and alternative </span><br>
<span style="background:white">conformations e.g. resulting
from binding to a
ligand), In addition, the </span><span style="background:white">sequence is subject to functional
constraints
due to the need to achieve </span><span style="background:white">catalytic activity and specific
interactions
with other molecules or </span><br>
<span style="background:white">chemical species (RNA,
proteins, DNA, ions..).
RNAs designed by nature and obtained by sequencing many
evolutionary
distinct organisms can be used to unveil the constraints
acting on RNA.
Combining this sequence data available in databases such as
RFAM with
statistical physics and computational methods will allow us
to reconstruct
the landscape associated to a given function and structure.
Our approach
will also be tested on well-controlled RNA sequence data
obtained from in vitro
selection (selex). In turn, we will exploit the
reconstructed landscapes
to design new RNA sequences, whose structural and functional
properties
will be experimentally tested. The latter scope is part of
the currently very active
field of design in material sciences, chemistry and
biomedicine.</span><br>
<br>
<br>
<span style="background:white"></span></span></p>
<p class="MsoNormal" style="text-align:justify;text-justify:inter-ideograph"><b><span>Practical
information:</span></b></p>
<p class="MsoNormal" style="text-align:justify;text-justify:inter-ideograph"><span>This
post-doc is
funded by the ANR Decrypted for 18 months and should start in
Spring 2021. The recruited postdoc will work in collaboration
with Simona Cocco
and Rémi Monasson, in the Statistical Physics and Inference
for Biology group
in the Laboratory of Physics of the Ecole Normale Supérieure.
She/he will also
benefit from the collaboration with Bruno Sargueil <span style="color:black">(</span></span><span lang="EN-US">CiTCoM, Paris
Descartes University </span><span>)
</span><span>and Yann Ponty <span style="color:black">(</span></span><span lang="EN-US">LIX, Ecole
Polytechnique </span><span>).</span><span></span></p>
<p class="MsoNormal" style="text-align:justify;text-justify:inter-ideograph"><span><br>
<br>
<b><span style="background:white">How to apply:</span></b></span></p>
<p class="MsoNormal" style="text-align:justify;text-justify:inter-ideograph"><span>The
candidate should
have a PhD (or have it completed before the start </span><span><br>
<span style="background:white">of the position) in a relevant
field, and a
strong experience in theoretical physics, statistical
physics or
bioinformatic and machine learning. To apply, please send a
CV and a cover
letter describing your interests and previous work to</span></span><span><a href="mailto:simona.cocco@phys.ens.fr" target="_blank"><span style="color:blue"> simona.cocco@phys.ens.fr</span></a><span style="background:white"> and </span><a href="mailto:remi.monasson@phys.ens.fr" target="_blank"><span style="color:blue">remi.monasson@phys.ens.fr</span></a><span style="background:white"></span></span>
</p>
<p class="MsoNormal"><span lang="EN-US"> </span></p>
<p class="MsoNormal"><b><span lang="EN-US">Bibliography:</span></b></p>
<p class="MsoNormal" style="text-autospace:none"><span>[1]Inverse Statistical Physics of Protein Sequences: A Key
Issues
Review.<b> </b>S. Cocco, C. Feinauer, M. Figliuzzi, R.
Monasson, M. Weigt. <a href="http://www.phys.ens.fr/~monasson/Articles/a107.pdf" target="_blank"><span style="color:#dca10d">Reports on Progress in Physics 81,
032601 (2018). </span></a></span></p>
<p class="MsoNormal" style="text-autospace:none"><span>[2] Direct-Coupling Analysis of nucleotide coevolution
facilitates RNA
secondary and tertiary structure prediction E. De Leonardis,
S. Lutz, S.
Ratz, S. Cocco, R. Monasson, A. Schug, M. Weigt <a href="http://www.phys.ens.fr/~monasson/Articles/a97.pdf" target="_blank"><span style="color:#dca10d">Nucleic Acid Research, doi:
10.1093/nar/gkv932 (2015)</span></a>
(<a href="http://www.phys.ens.fr/~monasson/Articles/a97-si1.pdf" target="_blank"><span style="color:#dca10d">supplemental text</span></a> and <a href="http://www.phys.ens.fr/~monasson/Articles/a97-si2.pdf" target="_blank"><span style="color:#dca10d">supplemental figures</span></a>) </span></p>
<p class="MsoNormal" style="text-autospace:none"><span>[3] <span><span>3D RNA and Functional Interactions from
Evolutionary Couplings.</span></span><span> Weinreb, C., Riesselman,
A.J., Ingraham,
J.B., Gross, T., Sander, C. and Marks, D.S. Cell 165(4), pp.
963–975 (2016). </span></span></p>
<p class="MsoNormal" style="text-autospace:none"><span>[4]<span> </span>An
evolution-based model for
designing chorismate mutase enzymes </span></p>
<p class="MsoNormal" style="text-autospace:none"><span>W.P. Russ, M. Figliuzzi, C. Stocker, P. Barrat-Charlaix,
M. Socolich, P.
Kast, D. Hilvert, R. Monasson, S. Cocco, M. Weigt, R.
Ranganathan <a href="http://www.phys.ens.fr/~monasson/Articles/a125.pdf" target="_blank"><span style="color:#dca10d">Science 369, 6502 (2020)</span></a></span></p>
<p class="MsoNormal" style="text-autospace:none"><span> </span></p>
<p class="MsoNormal"><span lang="EN-US"> </span></p>
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