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NA Digest, V. 20, # 24

NA Digest Thursday, June 25, 2020 Volume 20 : Issue 24


Today's Editor:

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

Today's Topics: Subscribe, unsubscribe, change address, or for na-digest archives: http://www.netlib.org/na-digest-html/faq.html

Submissions for NA Digest:

http://icl.utk.edu/na-digest/


From: Cleve Moler moler@mathworks.com
Date: June 15, 2020
Subject: A History of MATLAB, ACM Proceedings for HOPL IV


"A History of MATLAB", a 67-page paper that Jack Little and I have
written, has been published by the ACM in the proceedings of HOPL IV,
the Fourth ACM SIGPLAN History of Programming Languages Conference,
https://dl.acm.org/doi/10.1145/3386331. The conference, planned for
mid-June in London, has been postponed, but the proceedings have
arrived on schedule.

PACMPL in the ACM Digital Library is published with open access, so
the HOPL IV papers are freely available to ACM members and nonmembers
alike. In addition to MATLAB, the 19 papers in the HOPL IV volume
include histories of APL, C++, Clojure, Fortran coarrays, D, Emacs
Lisp, F#, Groovy, JavaScript, LabVIEW, Logo, Cambridge Polish,
Objective-C, Oz, R, S, Smalltalk, ML, and Verilog HDL.


From: Ahmad Abdelfattah ahmad@icl.utk.edu
Date: June 16, 2020
Subject: MAGMA is now on BitBucket using git


Due to the Mercurial support being discontinued on BitBucket starting
July 1st 2020, the public repository of the MAGMA library is now
converted to the git version control system. Active developers and
users of the library should switch to the new repository effective
immediately. All branches, issues, and release tags are also
converted. To clone a clean copy of MAGMA:

git clone git@bitbucket.org:icl/magma.git

The MAGMA library provides many dense and sparse linear algebra
algorithms for heterogeneous HPC systems that take advantage of many-
core architectures such as GPUs. For more information, please visit:
https://icl.utk.edu/magma.


From: Luca Paglieri luca.paglieri@polimi.it
Date: June 19, 2020
Subject: Modelling the Cardiac Function, ONLINE, Aug-Sep 2020


Deadline for abstract submission is July 20, 2020.

2020 iHEART Online Congress - Modelling the Cardiac Function August 31
- September 2, 2020 : https://iheart.polimi.it/mcf2020

This congress aims at highlighting the state of the art in the
mathematical modelling and numerical simulation of the cardiac
function and its clinical applications. Due to the ongoing situation
and foreseeable difficulties in global travelling, the congress will
be held online with live sessions. Scheduling times will be from
2p.m. to 6 p.m. CEST.

Confirmed plenary speakers:
- Olaf Dossel (Karlsruhe Institute of Technology)
- Francesco Migliavacca (Politecnico di Milano)
- Rajat Mittal (Johns Hopkins U.)
- Steven Niederer (King's College, London)
- Luca Pavarino (U. Pavia)
- Gernot Plank (U. Graz)
- Seiryo Sugiura (U. Tokyo)
- Natalia Trayanova (Johns Hopkins U.)
- Edward Vigmond (U. Bordeaux)

Contributed talks (15 minutes) are welcome.

For more information, registration and abstract submission, visit
https://iheart.polimi.it/mcf2020



From: Matthias J Ehrhardt m.ehrhardt@bath.ac.uk
Date: June 21, 2020
Subject: The Mathematics of Machine Learning, ONLINE, Aug 2020


The registration for the LMS-Bath Symposium on The Mathematics of
Machine Learning, 3-7 August 2020, https://mathml2020.github.io/ is
now open, see link (deadline 20 July 2020). The event was originally
scheduled to be run at the University of Bath but will now be run
online. Registration is on a first-come-first-serve basis, so
register soon to not miss out. Links to join the event will be send to
registered participants only.

Invited Speakers: Jonas Adler, Google DeepMind, UK; Simon Arridge,
University College London, UK; Erik Bekkers, Eindhoven University,
Netherlands; Martin Benning, Queen Mary University of London, UK;
Elena Calledoni, Norwegian University of Science and Technology,
Norway; Coralia Cartis, University of Oxford, UK; Yuejie Chi, Carnegie
Mellon University, USA; Lenaic Chizat, Laboratoire de Mathematiques
d'Orsay, France; Stephane Chretien, University of Lyon, France; Nadia
Drenska, University of Minnesota, US; Weinan E, Princeton University,
USA; Alhussein Fawzi, Google DeepMind, UK; Andrew Fitzgibbon,
Microsoft Research, UK; Anders Hansen, University of Cambridge, UK;
Varun Kanade, University of Oxford, UK; Benedict Leimkuhler,
University of Edinburgh, UK; Sofia Olhede, EPFL, Switzerland; Brynjulf
Owren, Norwegian University of Science and Technology, Norway; Marcelo
Pereyra, Heriot-Watt University, UK; Philipp Petersen, University of
Vienna, Austria; Johannes Schmidt-Hieber, University of Twente,
Netherlands; Carola-Bibiane Schonlieb, University of Cambridge, UK;
Aretha Teckentrup, University of Edinburgh, UK; Spencer Thomas,
National Physical Laboratory, UK; Matthew Thorpe, University of
Manchester, UK; Ivan Tyukin, University of Leicester, UK;
Pierfrancesco Urbani, Universite Paris-Saclay, France; Jong Chul Ye,
KAIST, Korea

Machine learning (ML) is currently undergoing a massive expansion, due
to the unprecedented availability of large amounts of data and
computational power. The last decade has seen tremendous improvements
in ML methods and achievements in many application areas including
(bio-) medical sciences, computer vision and finance to name but a
few. Remarkably, while ML relies on mathematical models and tools,
many ML algorithms do not have a rigorous mathematical foundation. One
reason for this is that ML has been historically developed as a
subfield of computer science rather than mathematics. Fundamental
analysis questions are open, such as convergence and convergence
rates, or the topology and geometry with which data should be
studied. It is essential that the mathematical community contributes
to ML and provides a solid underpinning of ML methods. This Symposium
will advocate the connection between ML and many mathematical
disciplines, such as numerical analysis, inverse problems,
optimisation, statistics, optimal transport, dynamical systems and
partial differential equations, in order to shed light into the
mysterious mathematical pathways of ML.


From: Svetozar Margenov margenov@parallel.bas.bg
Date: June 17, 2020
Subject: Large-Scale Scientific Computations, Bulgaria, Jun 2021


The 13th International Conference "Large-Scale Scientific
Computations" will take place in June 7-11, 2021, Sozopol, Bulgaria:
http://parallel.bas.bg/Conferences/SciCom21/

Topics: hierarchical, adaptive, domain decomposition and local
refinement methods; robust preconditioning algorithms; Monte Carlo
methods and algorithms; numerical linear algebra; control systems;
parallel algorithms and performance analysis; large-scale computations
of environmental, biomedical and engineering problems.

Plenary invited speakers: Yalchin Efendiev (Texas A&M University,
Colloge Station, TX, US); Xiaozhe Hu (Tufts University, MA, US); Oleg
Iliev, (ITWM, Kaiserslautern, DE); Mario Ohlberger, (University of
Munster, DE); Yuri Vassilevski, (Institute of Numerical Mathematics,
RAS, Moscow, Russia).

Applications for organizing special sessions are welcome till
September 30, 2020.

Conference chairman: Svetozar Margenov
Conference secretary: Silvia Grozdanova
E-mail: scicom21@parallel.bas.bg


From: Department of Computer Science, Hong Kong Baptist University
wwwadm@comp.hkbu.edu.hk
Date: June 22, 2020
Subject: Faculty Positions, Computer Science, HKBU


The Department of Computer Science at Hong Kong Baptist University,
presently offers BSc, MSc, MPhil, and PhD programmes, is now seeking
outstanding applicants for the following faculty positions on
tenure-track.

Professor / Associate Professor / Assistant Professor (Computer
Science) (PR0311/18-19)

The appointees will perform high-impact research; to teach and
supervise students at undergraduate and postgraduate levels, as well
as to contribute to professional and institutional
services. Collaboration with other faculty members in research and
teaching is also expected. They will be encouraged to collaborate with
colleagues within the Department to contribute to two special thematic
applications including (a) health informatics and (b) secure and
privacy-aware computing, and to pursue new strategic research
initiatives under the Department/Faculty/University.

Details: https://www.comp.hkbu.edu.hk/v1/?page=job_vacancies&id=503

Closing Date: 31 July 2020 (or until the positions are filled)


From: Irune Diaz Gonzalez recruitment@bcamath.org
Date: June 15, 2020
Subject: Research Technician Position, AI-Predict-COVID, BCAM


In the framework of the BCAM "Maths & Artificial Intelligence"
strategy, a series of projects in this field will be launched in
different areas of Applied Mathematics. This project is titled
"Machine learning for COVID- 19 predictions" and deals with the
development of supervised classification techniques that use
electronic health records to predict evolution of COVID-19 infections.

Requirements: Promising young researchers. Applicants must have their
Bachelor's or Master degree preferable in Computer Science,
Mathematics, Physics or related fields.

Skills and track-record: Good interpersonal skills; Demonstrated
ability to work independently and as part of a collaborative research
team; Ability to present and publish research outcomes in spoken
(talks) and written (papers) form; Ability to effectively communicate
and present research ideas to researchers and stakeholders with
different backgrounds; Fluency in spoken and written English.

Scientific Profile. The preferred candidate will have: Strong
background in numerical computing and data processing; Demonstrated
knowledge in machine learning techniques; Good programming skills in
Python or Matlab.

Aplications:
http://www.bcamath.org/en/research/job/ic2020-06-research-technician-ai-predict-covid
Deadline: 13th July, 14:00 (Spain)


From: Irune Diaz Gonzalez recruitment@bcamath.org
Date: June 15, 2020
Subject: Research Technician Position, Knowledge Transfer Unit, BCAM


Statistics (regression methods, time series, survival analysis,
multivariate analysis, clustering methods), Machine Learning
techniques (e.g.: neural networks, random forests, decision trees,
etc.) and optimization (e.g: discrete/stochastic optimization,
heuristics, combinatorics). About BCAM Knowledge Transfer Unit: The
aim of BCAM Knowledge Transfer Unit (KTU) is to develop mathematical
solutions for scientific challenges based on real-life applications.
One of BCAM's most important missions is to spread knowledge and
technology in the industry and the society in general. It is critical
for the Basque Center for Applied Mathematics to transfer the obtained
research results to sectors as biosciences, health, energy, advanced
manufacturing, telecommunications and transport, including local,
national and international entities. For further information, please
visit the website: http://www.bcamath.org/en/the-center/knowledge.

Requirements: Master's degree in Statistics, Computer Science, or a
closely related field. Strong background in Statistics and
Mathematics. Fluency in spoken and written Spanish and English.
Skills: Knowledge of advanced statistical methods and/or machine
learning techniques, data base management and data visualization;
Ability to analyse data, perform statistical analysis and interpret
results; Experience with statistical software packages and good
programming skills in R, Python and/or MATLAB and database management
systems (e.g: MySQL, MongoDB, etc.); Strong analytical and
problem-solving skills; Strong programming skills; Ability to read
scientific publications and implement mathematical algorithms; Good
interpersonal skills; Ability to effectively communicate and present
research ideas to researchers and stakeholders with different
backgrounds; Demonstrated high level written and oral communication
skills; Demonstrated ability to work independently and as part of a
collaborative research team. Principal duties and responsibilities:
Collaboration in knowledge transfer projects with industry and
research entities. Statistical and Machine Learning data analysis
consultation and participation in research projects, including: Data
processing, data management and data analysis; Writing code to analyse
data and produce results; Summarizing and interpreting data and
results; Preparing, producing, updating and automating reports;
Elaborating interim and final analysis of research projects; Assisting
and preparing presentations to stakeholders; Contribution to the
preparation and production of publications and report.

Apply at:
http://www.bcamath.org/en/research/job/ic2020-06-research-technician-ds-ktu
Deadline: 13th July, 2020. 14:00 SPAIN


From: Irune Diaz Gonzalez recruitment@bcamath.org
Date: June 18, 2020
Subject: Postdoc Position, Applied Statistics - COVID, BCAM


Development of mathematical/statistical methods and computational
tools for modelling the transmission dynamics of SARS-Cov-2 with a
special focus on the prediction of health care resources. Our proposal
rests on the combination of mechanistic models and Bayesian inference
for uncertainty quantification and the development of efficient Markov
Chain Monte Carlo (MCMC) samplers and numerical algorithms for the
real-time use of the results. The selected candidate will work with
members of the research lines of "Applied Statistics" and "Modelling
and Simulation in Life and Material Sciences" of the BCAM.

Requirements: Promising young researchers. Applicants must have their
PhD completed before the contract starts. PhD degree preferable in
Mathematics, Statistics or related fields.

Skills and track-record: Good interpersonal skills; A proven track
record in quality research, as evidenced by research publications in
top scientific journals and conferences; Demonstrated ability to work
independently and as part of a collaborative research team; Ability to
present and publish research outcomes in spoken (talks) and written
(papers) form; Ability to effectively communicate and present research
ideas to researchers and stakeholders with different backgrounds;
Fluency in spoken and written English.

Scientific Profile. The preferred candidate will have: Strong
background in Bayesian statistical modelling and inference; Background
in MCMC and Hamiltonian Monte Carlo is highly desirable; Good
programming skills in R, Python and/or C; Research experience in
applied Statistics in interdisciplinary applications.

Apply at: http://www.bcamath.org/en/research/job/ic2020-06-postdoctoral-fellowship-
covid-as
Deadline: 13th July, 2020. 14:00 SPAIN



From: Irune Diaz Gonzalez recruitment@bcamath.org
Date: June 18, 2020
Subject: Postdoc Position, Applied Statistics, BCAM


In the framework of the BCAM "Maths & Artificial Intelligence"
strategy, a series of projects in this field will be launched in
different areas of Applied Mathematics. This project is titled "Fair
Learning in Health" and deals with the development of mathematical
models aimed at detecting and ensuring non-discriminatory and fair
decisions based on artificial intelligence (AI) algorithms. Special
focus will be placed on health applications.

Requirements: Promising young researchers. Applicants must have their
PhD completed before the contract starts. PhD degree preferable in
Mathematics, Statistics or related fields.

Skills and track-record: Good interpersonal skills; A proven track
record in quality research, as evidenced by research publications in
top scientific journals and conferences; Demonstrated ability to work
independently and as part of a collaborative research team; Ability to
present and publish research outcomes in spoken (talks) and written
(papers) form; Ability to effectively communicate and present research
ideas to researchers and stakeholders with different backgrounds;
Fluency in spoken and written English.

Scientific Profile. The preferred candidate will have: Strong
background in mathematics/probability/statistics; Knowledge in
algorithmic fairness is desired; Good programming skills in R, Python
and/or C/C++; Interest and disposition to work in interdisciplinary
groups.

Apply at:
http://www.bcamath.org/en/research/job/ic2020-06-postdoctoral-fellowship-as
Deadline: 13th July, 2020. 14:00 SPAIN


From: Irune Diaz Gonzalez recruitment@bcamath.org
Date: June 15, 2020
Subject: Postdoc Position, Biomathematics, BCAM


Postdoctoral Fellowship in Biomathematics at the Mathematical and
Theoretical Biology Group

Requirements: We seek a highly motivated and skilled person, able to
work effectively as part of a team. Applicants must have their PhD
completed before the contract starts. PhD degree in applied
mathematics, mathematical biology, physics or related disciplines.

Skills and track-record: Good communication and interpersonal skills;
Fluent in English (verbal and written); Ability to communicate and
present research ideas to researchers with different background and
general public; Ability to clearly present and publish research
outcomes in spoken (talks) and written (papers) form; Programming in
LaTeX; Programming in C, MatLab or ; Ability to organize scientific
events (workshops, seminars, etc.).

Scientific Profile. The preferred candidate will have: research
experience and interest in mathematical modeling of infectious
diseases and population biology, dynamical systems theory, non-linear
dynamics, stochastic processes, complex systems and computer
programming; Experience in interdisciplinary research, formulation and
analysis of mathematical/computational models; knowledge of
bio-statistics and experience in advanced programming are advantage.

Apply at:
http://www.bcamath.org/en/research/job/ic2020-06-postdoctoral-fellowship-mtb
Deadline: July 13th, 2020. 14:00 SPAIN


From: FABRÍCIO SIMEONI DE SOUSA f.s.sousa@usp.br
Date: June 15, 2020
Subject: Postdoc Position, Computational Fluid Dynamics


Summary: The Center for Research in Mathematical Sciences Applied to
Industry (CEPID-CeMEAI) at University of Sao Paulo opens a
post-doctoral research position in Computational Fluid Dynamics. The
selected candidate will work at Institute of Mathematical and Computer
Sciences of the University of Sao Paulo in Sao Carlos/SP, Brazil. Sao
Paulo Research Foundation provides the financial support with a
monthly salary of BRL 7.373,10 (after taxes). Financial support can
also be provided to cover transportation expenses to move to Sao
Carlos - Brazil. An extra grant is also provided to cover
participation in highly relevant conferences and workshops, as well as
research trips (limited to 15% of the annual amount of the
fellowship). The position is for one year. Project: Multiscale
preconditioners for the simulation of petroleum
reservoirs. Supervisor: Fabricio Simeoni de Sousa Description: The
simulation of large oil reservoirs, such as those found in the
pre-salt layers of the Brazilian coast, require the use of
computational meshes of billions of elements, a scale that cannot be
handled efficiently with current commercial simulators. The use of
multiscale domain decomposition methods have shown great scalability
potential that allows an efficient parallelization of meshes with such
order of magnitude. Among the several methods found in the literature,
the Multiscale Robin Coupled Method (MRCM) has become a reference in
the area thanks to great flexibility introduced by the Robin boundary
conditions and the independent choice of interface spaces. The present
project aims the development and implementation of an efficient
preconditioner based on the MRCM in a high performance computing
environment taking advantage of its modern hybrid multicore
architecture. The final goal is to accelerate large-scale simulators
capable of handling meshes with billions of elements, required for the
accurate simulation of large petroleum reservoirs. Professor Sousa
will lead the research, jointly with his research group.
Requirements: Applicants should have PhD in Applied Mathematics,
Computer Sciences, or related fields, with experience in Computational
Fluid Dynamics. Experience in the implementation of multiscale methods
for reservoir simulation is required. We also require experience with
order reduction methods for subsurface flows problems and experience
in high performance computing with C/C++ languages. At least two
scientific journal paper published in the last 5 years in the field of
multiscale methods for reservoir simulation are required. Candidates
must have got their PhD in the last 5 years to be considered for this
position. Application: Please send your application before July 15,
2020 to: Dr. Fabricio Simeoni de Sousa (f.s.sousa@usp.br). Please
indicate "CEPID Postdoc - Multiscale Methods" in the subject
line. Applications should include curriculum vitae, statement of
research interests and contact information of two researchers for
recommendation letters (only PDF files). Contract Condition: Grant
from FAPESP under the Research, Innovation and Dissemination Centers
(RIDC-CeMEAI) (http://www.fapesp.br/en/17,
http://www.cemeai.icmc.usp.br/).



From: Isabel Figueiredo isabelf@mat.uc.pt
Date: June 19, 2020
Subject: Postdoc Position, Computational Mathematics, Univ of Coimbra


Postdoctoral position in computational mathematics (focusing on image
processing and analysis, visualization, numerical analysis,
optimization, inverse problems in imaging, partial differential
equations - with applications in medicine) in the framework of the
interdisciplinary research project "Multi-Cam Capsule Endoscopy
Imagery: 3d Capsule Location and Detection of Abnormalities", with
reference POCI-01-0145-FEDER-028960, of FCT - Portuguese national
funding agency for science, research and technology
(https://www.fct.pt/index.phtml.en)

Location : Department of Mathematics, Faculty of Sciences and
Technology, University of Coimbra (Coimbra) Portugal.
Duration : 1 year (possible extension - extra 1 year).
Starting date : October 2020.
Applications : July 03 - July 16, 2020.

Detailed information : http://www.mat.uc.pt/~isabelf/Postdoccall2020.html
Official announcement : http://www.eracareers.pt/opportunities/index.aspx?
task=global&jobId=124887



From: Roderick Melnik rmelnik@wlu.ca
Date: June 19, 2020
Subject: Postdoc Position, M3AI Lab/MS2Discovery, WLU, Waterloo, Canada


Applications are invited for a Postdoctoral Position in Modeling for
Complex Systems, with focus on life science applications in
data-driven environments. The successful candidate will be part of
the research program in mathematical modeling and computational & data
sciences at the Laurier M3AI Lab and MS2Discovery Institute in
Waterloo, Canada. Further information about the position and how to
apply can be found at the following website:

http://m2netlab.wlu.ca/research/current-openings.html

The position is available from October 1, 2020. The review of
applications will begin immediately and continue until the position is
filled.



From: Raphael Kruse raphael.kruse@mathematik.uni-halle.de
Date: June 25, 2020
Subject: Postdoc Position, MLU Halle-Wittenberg


The Martin-Luther-University Halle-Wittenberg, Institute of
Mathematics, is offering a position as a Postdoctoral Fellow (m-f-d)
in full time, limited for 3 years.

The position is offered within the DFG funded research unit FOR 2402,
project P3 "Numerical analysis of rough PDEs".

Requirements include a successfully completed PhD degree in
mathematics; a strong background in numerical analysis and stochastic
analysis of stochastic evolution equations; experience in teaching and
organizing university level courses in mathematics; good programming
skills (preferably in Python); very good command of the German and/or
English language.

For the complete announcement, please go to
http://www.verwaltung.uni-halle.de/dezern3/Ausschr/20_5_825_20_H_neu_engl.pdf

The job reference number is 5-825/20-H.

For further information, please contact Raphael Kruse, raphael.kruse
(at) mathematik.uni-halle.de


From: Andreas Carlson acarlson@math.uio.no
Date: June 25, 2020
Subject: PhD Position, Computational Fluid Mechanics, Univ of Oslo


A PhD position is available at the University of Oslo at the
Mathematics Department in the field of; computational fluid
mechanics/applied mathematics/droplet flow.

Access to fresh water is the foundation for life on Earth that poses
severe restrictions and requirements for life in regions that
contended with water scarcity. A fog net is a low cost, efficient and
simple technology for harvesting water from the atmosphere. The goal
of this project is to develop a novel fog net, where the planned work
will involve development of theoretical/mathematical models, numerical
tools and computational investigations of capillary flow of droplet on
poro-elastic materials.

More details:
https://www.jobbnorge.no/en/available-jobs/job/189245/phd-research-fellowship-in-fluid-
mechanics-droplet-flow



From: David Cohen david.cohen@chalmers.se
Date: June 25, 2020
Subject: PhD Position, Computational Mathematics for SPDEs, Gothenburg


The Department of Mathematical Sciences at Chalmers University of
Technology and the University of Gothenburg invites applications for
one PhD position in Mathematics with focus on computational analysis
of stochastic partial differential equations.

Application deadline: October 09, 2020.

For more information, please visit
https://www.chalmers.se/en/about-chalmers/Working-at-
Chalmers/Vacancies/Pages/default.aspx?rmpage=job&rmjob=8672&rmlang=UK



From: Hannah Rittich h.rittich@fz-juelich.de
Date: June 25, 2020
Subject: PhD Position, Numerical Methods for HPC, JSC, Germany


The Julich Supercomputing Centre at Forschungszentrum Julich (Germany)
is offering a position for a PhD candidate beginning as soon as
possible. The topic is on Parallel Simulations of Phase-Field
Problems. The successful applicant will work on enhancing numerical
methods for these problems, to suit the needs of modern supercomputer
architectures. An applicant should have acquaintance with numerical
methods and algorithms. Furthermore, they should be proficient in
writing numerical software, preferably in C++ and Python.

For more information see: https://is.gd/LLFgB6


From: Tobias Breiten breiten@math.tu-berlin.de
Date: June 25, 2020
Subject: PhD Position, TU Berlin, Germany


The Technical University of Berlin, Institute of Mathematics, invites
applications for a PhD student (m-f-d) in full time, for a period of
max. 5 years. The research is at the interface of control theory and
optimization with partial differential equations, in particular
feedback control and minimum energy estimation.

Requirements are successfully completed university degree (Master,
Diplom or equivalent) in mathematics; detailed knowledge in the areas
of control theory, optimization with partial differential equations,
numerical methods and model reduction, documented by very good grades;
teaching experience with tutorials or exercise sessions; good command
of German and English, both written and spoken, willingness to acquire
lacking language skills.

Application deadline: July 24th, 2020.

For the full advertisement, please go to
https://stellenticket.de/80745/TUB/?lang=en

For further information, please contact Tobias Breiten, breiten (at)
math.tu-berlin.de


From: Enrique S. Quintana-Orti quintana@disca.upv.es
Date: June 22, 2020
Subject: PhD Position, Univ Politecnica de Valencia


A three-year contract for a PhD position is offered for students
interested in deep learning, computer architecture, high performance
computing, and energy consumption.

Requisites for the candidates: a) Possess a bachelor university degree
or the equivalent in your country, by a non-Spanish institution, in
Computer Science or Computer Engineering, having completed the studies
after January 1, 2016. b) Meet the academic requirements necessary
for admission to a doctoral program at the time of selection, and be
admitted to a doctoral program at the time of hiring. c) Possess a
knowledge of Spanish or English, at the level of conversation,
suitable for the development of research work.

The salary is in the level of a PhD fellowship in any Spanish
institution. Further details on the application process here:
http://www.upv.es/entidades/SRH/conypi/1128178normalc.html (sorry,
only in Spanish) or by contacting Prof. Enrique S. Quintana-Orti by
mail (quintana@disca.upv.es).

Deadline for application: July 7, 2020.


From: Christian Schulz christian.schulz@univie.ac.at
Date: June 15, 2020
Subject: PhD Positions, Algorithm Engineering, Heidelberg


You love algorithms, their analysis and efficient implementation? You
are about to or know somebody who graduates with an excellent Master's
degree and is looking for a PhD position? Then please read on:

The newly established research group with focus on algorithm
engineering led by Christian Schulz at the University of Heidelberg,
Germany, is inviting applications for two fully funded full-time
positions of a PhD Student / University Assistant (m/f) starting on
October 1st, 2020 (the exact date is negotiable). The initial
contract length is two years, but an extension is highly expected.

Working Area: A successful candidate will work under the supervision
of Christian Schulz on the topics of algorithm engineering, parallel
and distributed algorithms in particular for practical data reduction
and graph partitioning problems. Further responsibilities as part of
the position include the supervision of bachelor and master students
and TA duties.

Requirements: Very good university degree (Master or equivalent) in
computer science or a related field; Solid skills in software
development and in the theoretical analysis of algorithms (evidenced
by your thesis or relevant courses); knowledge in combinatorial
algorithms and linear algebra is particularly desirable;
Self-motivation, team spirit and willingness to work in
interdisciplinary projects; Knowledge in parallel programming (in
particular MPI) is a plus, but no requirement.

Please forward this email to anyone who may be interested or send your
application documents (cover letter, CV, copies of certificates, a
skype address for a possible interview and the contact information of
two references if available) to the address below. To receive full
consideration, submit the documents via email by July 15, 2020 to:
christian.schulz@univie.ac.at


From: Ruming Zhang ruming.zhang@kit.edu
Date: June 16, 2020
Subject: PhD Positions, Applied Mathematics, Karlsruhe Inst of Technology


The project "High order numerical methods for acoustic scattering
problems with locally perturbed periodic structures" is funded by the
German Research Foundation (DFG), starts on October 01, 2020. The aim
of this project is to design high order numerical methods to simulate
time- harmonic acoustic scattering problems, which are modelled by
Helmholtz equations, in three-dimensional spaces. Numerical analysis
and numerical experiments will be carried out to investigate both the
convergence and efficiency of the newly proposed numerical methods.

We seek for an ambitious doctoral researcher with strong interest in
the numerical methods for partial differential equations. The position
is to be started on October 01, 2020. You will have the opportunity to
attend conferences, workshops and summer schools. Engagement in
teaching is encouraged.

Please apply using the following link:
http://www.pse.kit.edu/karriere/joboffer.php?id=34389&language=en


From: Frank Knoben admin@igpm.rwth-aachen.de
Date: June 15, 2020
Subject: PhD Positions, Mathematics Department, RTWH Aachen, Germany


At the Department of Mathematics of the RWTH Aachen University we
offer ten part time (75%) ph.d. positions limited to three years. The
positions are to be filled on 01.09.2020 Closing date 5th July 2020.

For full details, please see:
https://www.rwth-aachen.de/cms/root/Die-RWTH/Arbeiten-an-der-
RWTH/Jobboerse/~kbag/JOB-Einzelansicht/file/31853/
or contact fachgruppensprecher@mathematik.rwth-aachen.de


From: Carlos Fonseca cmdafonseca@hotmail.com
Date: June 16, 2020
Subject: CFP, Combinatorial Matrices


COMBINATORIAL MATRICES, by Special Matrices

This special issue is devoted to combinatorial matrices. Combinatorial
matrices cover all type of matrices involving some combinatorial
information related to specific patterns, permutations and
combinatorics in general, Hadamard matrices, Hadamard designs, Latin
squares, graph theory, or alternating sign matrix, among others, and
their linear algebraic properties.

GUEST EDITORS:
- Wenchang Chu, Universita del Salento, Lecce, Italy;
wenchang.chu@unisalento.it
- Emrah Kilic, TOBB University of Economics and Technology, Ankara,
Turkey; ekilic@etu.edu.tr
- Helmut Prodinger, Stellenbosch University, Matieland, South Africa;
hproding@sun.ac.za

All manuscripts are subject to the standard peer review process before
publication.

Manuscripts should be submitted via
http://www.editorialmanager.com/spma.

When entering your submission (via online submission system), please
choose the option "SI - Combinatorial Matrices".

Deadline for submissions: October 31th, 2020



From: Marion Weinzierl SORSE.enquiries@gmail.com
Date: June 25, 2020
Subject: CFP, International Series of Online Research Software Events


The international Series of Online Research Software Events (SORSE)
has opened their call for contributions:
https://sorse.github.io/programme/call-for-contributions/

With the cancellation of several international Research Software
Engineering (RSE) community events as a result of the COVID-19
pandemic, RSEs worldwide are facing a lack of opportunities to engage
with their wider community. To address this challenge, SORSE has been
launched by an international committee to provide an opportunity for
RSEs to develop and grow their skills, build new collaborations and
engage with RSEs worldwide. Until we can meet again in person, SORSE
(pronounced "Source"), will bridge the gap and be the source of
interesting and engaging events.

This is an open call to all RSEs and anyone involved with research
software, worldwide, to propose talks, workshops and other types of
online events.

The Call for Contributions form will remain open continuously and
there will be a rolling deadline at the end of the last day (UTC) of
each month, following which all contributions received over the
previous month will be sent for review by the Programme Committee.


From: Brezinski Claude claude.brezinski@univ-lille.fr
Date: June 17, 2020
Subject: Contents, Numerical Algorithms, 84 (3)


Table of Contents
Numerical Algorithms, Vol. 84, No. 3

Optimizations of a fast multipole symmetric Galerkin boundary element
method code. Anicet Dansou, Saida Mouhoubi, Cyrille Chazallon

Two-step inexact Newton-type method for inverse singular value
problems. Wei Ma, Xiao-shan Chen

An explicit six-step singularly P-stable Obrechkoff method for the
numerical solution of second-order oscillatory initial value problems.
Mehdizadeh Khalsaraei, Ali Shokri

Condition numbers of the multidimensional total least squares problems
having more than one solution. Lingsheng Meng, Bing Zheng, Yimin Wei

Reconstruction algorithms of an inverse source problem for the
Helmholtz equation. Ji-Chuan Liu, Xiao-Chen Li

Family weak conjugate gradient algorithms and their convergence
analysis for nonconvex functions. Gonglin Yuan, Xiaoliang Wang, Zhou
Sheng

A convergence study for reduced rank extrapolation on nonlinear
systems. Avram Sidi

An ADMM-based scheme for distance function approximation. Alexander
Belyaev, Pierre-Alain Fayolle

On the convergence analysis of the gradient-CQ algorithms for the
split feasibility problem. Suparat Kesornprom, Nattawut Pholasa,
Prasit Cholamjiak

A second-order artificial compression method for the evolutionary
Stokes-Darcy system.

Generation of point sets by convex optimization for interpolation in
reproducing kernel Hilbert spaces. Ken'ichiro Tanaka

Fast conservative numerical algorithm for the coupled fractional
Klein-Gordon-Schroedinger equation. Meng Li, Chengming Huang,
Yongliang Zhao

An adaptive local discontinuous Galerkin method for nonlinear
two-point boundary-value problems. Mahboub Baccouch

Numerical approximation of the fractional Cahn-Hilliard equation by
operator splitting method. Shuying Zhai, Longyuan Wu, Jingying Wang,
Zhifeng Weng

Computers in mathematical research: the study of three-point
root-finding methods. Ivan Petkovic, Dorde Herceg

Recursive blocked algorithms for linear systems with Kronecker product
structure. Minhong Chen, Daniel Kressner

Generalized viscosity implicit scheme with Meir-Keeler contraction for
asymptotically nonexpansive mapping in Banach spaces. Rajat Vaish,
Kalimuddin Ahmad


End of Digest
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