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NA Digest, V. 20, # 22

NA Digest Sunday, June 07, 2020 Volume 20 : Issue 22


Today's Editor:

Daniel M. Dunlavy
Sandia National Labs
dmdunla@sandia.gov

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From: John Butcher butcher@math.auckland.ac.nz
Date: June 01, 2020
Subject: Robert Chan, 1943-2020


I am sorry to announce the death of Dr Robert Peng Kong Chan on 19 May
2020 at the age of 76. Robert was born in Malaya and migrated to New
Zealand at an early age. He studied Physics and Mathematics at the
University of Auckland and obtained his PhD in 1989 under the
supervision of Kevin Burrage and John Butcher. After an early career
as a secondary school teacher, Robert was appointed to an academic
position at the University of Auckland and retired in 2016 as a Senior
Lecturer. His research was centred on the use of symmetrisers for
passive and active extrapolation in the solution of ordinary
differential equations. He supervised a number of doctoral and masters
students. He is remembered as a kind and patient teacher and a
warm-hearted colleague.



From: Cornelis W. Oosterlee c.w.oosterlee@cwi.nl
Date: June 02, 2020
Subject: ONLINE, ML in Quantitative Finance and Risk Management, Jul 2020


Announcement for an On-line One-day Workshop, Machine Learning in
Quantitative Finance and Risk Management, Thursday July 2nd 2020,
organised by Kees Oosterlee and Kristoffer Andersson (CWI, Amsterdam).

The workshop times are CET, Central European Time:

10:00 AM: (Keynote) Christoph Reisinger (U. Oxford): "Deep xVA solver
-- A neural network based counterparty credit risk management
framework"
11:00 AM Kristoffer Andersson, (CWI): “Learning exposure profiles for
portfolios of exotic derivatives”
11:50 AM: Shashi Jain (IISc Bangalore): "Universal static hedging
using a shallow neural network"

13:30PM: Anastasia Borovykh (Imperial College, London): “To interact
or not? On the convergence properties of interacting particle
optimization”
14:20PM: Shuaiqiang Liu, (TU Delft): "Deep learning for large
time-step simulations of stochastic differential equations"
15:15PM: (Keynote) Yuying Li (U. Waterloo, Canada): "Asset allocation
without pain: learning dynamic strategies directly from market
data"

This workshop will take place, on-line, via zoom.us. See
https://www.cwi.nl/research/groups/scientific-computing/events/workshop-machine-
learning-in-quantitative-finance-and-risk-management
for the log-in details.



From: Alexander Brune acb795@bham.ac.uk
Date: June 05, 2020
Subject: RESCHEDULED, BECMC 2020, Jul 2020


The British Early Career Mathematicians’ Colloquium 2020 will now be
held as a virtual conference on the 14th-15th July 2020. This will be
a two-day event aimed at PhD students and early career mathematicians,
which is free to attend. It offers participants a valuable opportunity
to network with others in their field, and gain an insight into the
active areas of research in a wide range of mathematical
disciplines. We are working on making the online conference as
accessible as possible, which includes providing auto captioning.

To find out more and register, please email the committee on
becmc2020@contacts.bham.ac.uk.


From: Willy Dörfler willy.doerfler@kit.edu
Date: June 05, 2020
Subject: ONLINE Summer School, Computational Photonics, Sep 2020


In this one week summer school world leading experts from both
mathematics and theoretical physics give a concise introduction to
important concepts and recent developments in the field of
Computational Photonics. The lectures will be complemented by computer
tutorials to provide insights into the implementation and performance
of various algorithms.

It will probably be held online but we are also planning for a hybrid
event or even an on-site event in case this will be possible. For
more details see http://www.waves.kit.edu/summerschool2020.php

Speakers: Sven Burger (ZIB Berlin), Christin David (U Jena), Andrei
Lavrinenko (DTU Denmark), Owen Miller (Yale), Lothar Nannen (TU
Vienna), Philipp Schneider (ZIB Berlin), Ole Sigmund (DTU Denmark),
Barbara Verfurth (U Augsburg).

Online application is open. Please note that the number of
participants is limited. There is no fee.



From: Jed Brown jed.brown@colorado.edu
Date: June 07, 2020
Subject: RSE Position, Extreme-scale simulation of composite inelastic

media, CU Boulder

CU Boulder's PSAAP Multidisciplinary Simulation Center has an opening
for a Research Software Engineer to co-lead development of robust,
extensible open source software for extreme-scale simulation of
large-deformation composite poro-elasto-visco-plastic media across a
broad range of regimes with experimental validation and coordination
with micromorphic multiscale models.

Successful applicants will have strong written and verbal
communication skills, experience in some of the following topics, and
interest in learning the others: collaborative software development
and devops (Git, continuous integration, etc.); maintainable,
high-performance programming techniques for CPUs and GPUs; finite
element and material-point discretizations; computational
mechanics/inelasticity; parallel algebraic solvers such as PETSc;
scalable data-intensive computing.

The position can start as soon as July 1 and is remote-friendly,
especially during the pandemic. US citizenship or permanent residency
is preferred. Minimum requirement: non-sensitive country foreign
national. To apply, please send a CV, cover letter, and contact
information for three references to jed.brown@colorado.edu and
richard.regueiro@colorado.edu. The University of Colorado Boulder is
committed to building a culturally diverse community of faculty,
staff, and students dedicated to contributing to an inclusive campus
environment. We are an Equal Opportunity employer, including veterans
and individuals with disabilities. We offer a competitive salary and
a comprehensive benefits package.



From: Jed Brown jed.brown@colorado.edu
Date: June 07, 2020
Subject: Postdoc Position, Extreme-scale simulation of composite

inelastic media, CU Boulder

CU Boulder's PSAAP Multidisciplinary Simulation Center has an opening
for a Postdoctoral Associate to develop algorithms for extreme-scale
simulation of large-deformation composite poro-elasto-visco-plastic
media across a broad range of regimes, validation and rapid
calibration using experimental data, and micromorphic multiscale
models with uncertainty quantification.

Successful applicants will have strong written and verbal
communication skills, experience in some of the following topics, and
interest in learning the others: collaborative software development
and devops (Git, continuous integration, etc.); maintainable,
high-performance programming techniques for CPUs and GPUs; finite
element and material-point discretizations; computational
mechanics/inelasticity; multiscale modeling techniques; parallel
algebraic solvers such as PETSc; and scalable data-intensive computing
and uncertainty quantification.

The position can start as soon as July 1 and is remote-friendly,
especially during the pandemic. US citizenship or permanent residency
is preferred. Minimum requirement: non-sensitive country foreign
national. To apply, please send a CV, cover letter, and contact
information for three references to jed.brown@colorado.edu and
richard.regueiro@colorado.edu. The University of Colorado Boulder is
committed to building a culturally diverse community of faculty,
staff, and students dedicated to contributing to an inclusive campus
environment. We are an Equal Opportunity employer, including veterans
and individuals with disabilities. We offer a competitive salary and
a comprehensive benefits package.



From: Heike Sill heike.sill@wias-berlin.de
Date: June 04, 2020
Subject: Postdoc Position, Optimization with PDEs, WIAS, Germany


WIAS invites in the Research Group ”Nonsmooth Variational Problems and
Operator Equations” (Head: Prof. Dr. M. Hintermüller) applications for
a Research Assistant Position (f/m/d) (Ref. 20/11). to be filled at
the earliest possible date.

Field of work: Optimization with partial differential equations. The
holder of the position is qualified in a modern field of optimization
with partial differential equations. Of particular inter-est are
non-smooth coupled systems and data-driven (e.g. machine learning)
approaches to modeling and optimization or variational problems in
mathematical image processing. In addi-tion to analytical
considerations, the development and implementation of numerical
solution methods are of central importance.

Wanted: A motivated, outstanding young researcher with a very good
degree and excellent doctorate in mathematics as well as previous
experience in the fields mentioned above with the willingness to take
on responsibility for interdisciplinary projects. Further experience
with-in the framework of independent research in a postdoctoral phase
as well as very good knowledge in the areas of
- Optimal control with partial differential equations and numerical
solution methods,
- Quasivariation inequalities,
- Non-smooth variation problems, e.g. with applications in image
processing as well as experience in the computer-aided realization
of the associated numerical solution methods. This position is
associated with the production of publications in international
peer-reviewed journals, presentation of the results at international
conferences and co-support of students working at WIAS in this field
as bachelors, masters or doctoral students.

See here for more information: https://short.sg/j/6874006



From: Marta D'Elia mdelia@sandia.gov
Date: June 04, 2020
Subject: Postdoc Position, Sandia National Laboratories, Livermore, CA


A postdoctoral position is available at Sandia National Laboratories
in Livermore, California, starting in October 2020. We are looking for
creative problem solvers with knowledge of nonlocal and/or fractional
modeling and, more generally, with experience in scientific computing.
The project at hand primarily involves the design of new models and
algorithms for the simulation of heterogeneous materials and media in
the context of nonlocal mechanics and subsurface anomalous diffusion.
The project also includes the design and implementation of efficient
optimization solvers for the same models. Other avenues of research
include uncertainty quantification and scientific machine learning,
with special focus on applications in computational modeling of
physical systems.

Interested candidates should apply at
https://cg.sandia.gov/psc/applicant/EMPLOYEE/HRMS/c/HRS_HRAM_FL.HRS_CG_SEARCH_F
L.GBL?Page=HRS_APP_SCHJOB_FL&Action=U
by selecting JOB ID #672035. For specific questions, please contact
mdelia@sandia.gov.

Qualifications we require: PhD in the applied mathematics,
computational science or engineering; Experience, knowledge and
expertise in nonlocal/fractional modeling; Experience, knowledge and
expertise in computational science and code development.

Qualifications we desire: Knowledge of finite element methods;
Knowledge of uncertainty quantification and machine learning;
Knowledge of optimization; Expertise in C/C++ and/or Python.



From: Felix Lucka Felix.Lucka@cwi.nl
Date: June 03, 2020
Subject: PhD Position, Computational Imaging, CWI, Amsterdam


The Centrum Wiskunde & Informatica (CWI) has a vacancy in the
Computational Imaging research group for a talented PhD student, on
the subject of “Translation-Driven Development of Deep Learning for
Simultaneous Tomographic Image Reconstruction and Segmentation”. The
project starts in October, more information can be found at

https://www.cwi.nl/jobs/vacancies/phd-student-on-the-subject-of-201ctranslation-driven-
development-of-deep-learning-for-simultaneous-tomographic-image-rec\
onstruction-and-segmentation



From: Gerlind Plonka-Hoch plonka@math.uni-goettingen.de
Date: June 04, 2020
Subject: PhD Positions, Applied Mathematics, Univ Goettingen


The Research Training Group RTG 2088 "Discovering Structure in Complex
Data" at the Georg- August-University Goettingen offers two positions
for Ph.D. candidates beginning a soon as possible. The salary is in
accordance with the German public service salary scale (E13 TV-L) with
75 % for up to three years.

The research projects in this RTG focus on new mathematical concepts
in statistics, optimization, and inverse problems. Detailed
information for the PhD positions can be found at
https://www.uni-goettingen.de/de/305402.html?cid=100683

Information about the RTG can be found on the homepage
https://www.uni-goettingen.de/de/514290.html

Deadline for application is June 22, 2020.



From: Daniela di Serafino daniela.diserafino@unicampania.it
Date: June 04, 2020
Subject: PhD Positions, Maths, Physics & Applications for Engineering, Italy


The call for admission to the PhD Program in Mathematics, Physics and
Applications for Engineering at the Department of Mathematics and
Physics of the University of Campania “L. Vanvitelli, Italy, is
open. 8 fully funded PhD positions (4 reserved to graduate students
from foreign universities) plus 2 non-funded ones are
available. Highly motivated graduate students interested in
Computational Mathematics are warmly invited to apply.

Detailed information and the application procedure (in English and
Italian) can be found at
https://www.unicampania.it/index.php/didattica/dottorati-di-ricerca/iscriversi-ad-un-
dottorato
clicking on MATEMATICA, FISICA E APPLICAZIONI PER
L’INGEGNERIA. Application deadline is June 30, 2020.



From: Alex Beaumont alex.beaumont@oup.com
Date: June 02, 2020
Subject: Contents, Information and Inference, 9 (2)


Information and Inference: A Journal of the IMA
Links to all articles in the issue are available online at:
https://academic.oup.com/imaiai/issue/9/2

A prototype knockoff filter for group selection with FDR control,
Jiajie Chen, Anthony Hou, Thomas Y Hou

Non-convex low-rank matrix recovery with arbitrary outliers via
median-truncated gradient descent, Yuanxin Li, Yuejie Chi, Huishuai
Zhang, Yingbin Liang

Network topology inference using information cascades with limited
statistical knowledge, Feng Ji, Wenchang Tang, Wee Peng Tay, Edwin K P
Chong

Robust 1-bit compressed sensing via hinge loss minimization, Martin
Genzel, Alexander Stollenwerk

Near-optimal recovery of linear and N-convex functions on unions of
convex sets, Anatoli Juditsky, Arkadi Nemirovski

Analysis of hard-thresholding for distributed compressed sensing with
one-bit measurements, Johannes Maly, Lars Palzer

Size-independent sample complexity of neural networks, Noah Golowich,
Alexander Rakhlin, Ohad Shamir

Erratum to: Robust 1-bit compressed sensing via hinge loss
minimization, Martin Genzel, Alexander Stollenwerk

End of Digest
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