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NADIGEST  June 2019, Week 3

NADIGEST June 2019, Week 3


NA Digest, V. 19, # 24


NA Digest Editor <[log in to unmask]>


NA-Digest <[log in to unmask]>


Sun, 16 Jun 2019 16:38:24 -0400





text/plain (889 lines)

Subject: NA Digest, V. 19, # 24

NA Digest  Sunday, June 16, 2019  Volume 19 : Issue 24

Today's Editor:

	Daniel M. Dunlavy
	Sandia National Labs
	[log in to unmask]

Today's Topics:

	John G. Lewis
	Deadline Extended: Sparse Days, France, Jul 2019
	Uncertainty Quantification, Machine Learning & Bayesian Statistics, Germany, Jul 2019
	Inverse Problems from Theory to Application, UK, Sep 2019
	Mathematics Meet Pharmacy, Czech Republic, Sep 2019
	Controlling Delayed Dynamics, Italy, Nov 2019
	Mid-Atlantic NA-Day, USA, Nov 2019
	Domain Decomposition Methods, Hong Kong, China, Dec 2019
	ICOSAHOM 2020, Austria, Jul 2020
	Faculty Positions, Computational Sciences, All Levels
	Research Position, Software for Complex Combinatorial Problems
	Research position, Algorithms and Software for Graph and Tensor Computing
	Postdoc Position, Lawrence Berkeley National Laboratory
	Postdoc Position, Machine Learning, Univ of Reading
	Postdoc Position, Mathematics, Univ of Campinas, Brazil
	Postdoc Position, Uncertainty in digital twin engineering, Univ of Liverpool
	Postdoc Positions, Computer Vision/Optimization/Inv Problems, SZU
	PhD Position, Geometric Deep Learning Simula-UCSD-UiO PhD Program
	PhD Position, Maxwell-LLG Equations
	PhD Position, Multiscale Analysis of Potential Fields, TU Bergakademie Freiberg
	PhD Positions, Simulation Technology, Univ of Stuttgart
	Contents, Acta Cybernetica, 24 (1)
	Contents, Journal of Numerical and Applied Mathematics, 130 (1)
	Contents, Statistics, Optimization and Information Computing, 7 (2)

Subscribe, unsubscribe, change address, or for na-digest archives:

Submissions for NA Digest:


From: Dianne Prost O'Leary [log in to unmask]
Date: June 13, 2019
Subject: John G. Lewis

John G. Lewis died peacefully in his sleep on June 10, about three
years after a diagnosis of ALS.

After teaching at St. Olaf College in Minnesota, John studied computer
science at Stanford University, completing his PhD dissertation on the
Lanczos algorithm in 1976. He taught at Johns Hopkins University
before moving to Boeing Computer Services, retiring as a Technical
Fellow, and then to Cray Inc. He worked with Iain Duff and Roger
Grimes to compile the Boeing Sparse Matrix Collection, hugely
influential in the development of mathematical software. He also
contributed many high-quality algorithms for sparse matrix
problems. He was part of a team awarded the ACM Gordon Bell Prize in

His friends remember John for his integrity, his passion for the
outdoors, and his untiring activity, right up until his death, for
social justice and the environment.

He is especially missed by his wife Fran, sons Steven and David, and
two grandchildren.

Jason Wu
Dianne O'Leary


From: Iain Duff [log in to unmask]
Date: June 14, 2019
Subject: Deadline Extended: Sparse Days, France, Jul 2019

The Annual Sparse Days meeting will be held at CERFACS in Toulouse on
11 and 12 July 2019.  The deadline for registration is 21st June using
the web site

As usual, there is no registration fee but interested parties should
register using the website.  Please do register before the 21st June
since it will greatly help our organization. When you register, you
should indicate whether you want to give a talk and whether you want
to attend our traditional conference dinner on the evening of Thursday
11th. The dinner will be held at Les Caves de la Marechale (free of
charge for students, 22 euros for non-students, 43 euros for extra

The normal length for the talk and questions is 30 minutes but this is
open to negotiation in either direction subject to the fact that as
usual we will not be having parallel sessions.

For participants wanting to go to the ICIAM meeting in Valencia there
is a summer scheduled flight on Easyjet that flies non-stop to
Valencia leaving Toulouse at 11.45 on Sunday 14th.  If you are worried
about your carbon footprint there is a regular train service or you
can drive; both options taking around 7.5 hours.


From: Robert Scheichl [log in to unmask]
Date: June 12, 2019
Subject: Uncertainty Quantification, Machine Learning & Bayesian Statistics, Germany, Jul 2019

International Workshop on *Uncertainty Quantification, Machine
Learning & Bayesian Statistics in Scientific Computing* Heidelberg
University, 1st-5th July 2019 Website:

There is no fee associated with this workshop! You can register at:

The workshop is sponsored by Mathematics Center Heidelberg (MATCH) and
by the Heidelberg Graduate School of Mathematical and Computational
Methods for the Sciences (HGS MathComp) and forms part of the MATCH
Thematic Semester with the same title.

The aim of the workshop is to bring together researchers working in
Uncertainty Quantification, Machine Learning and Bayesian Statistics
with a particular focus on high- and infinite-dimensional problems
from scientific computing, where the sparsity or uncertainty of data
requires an integration of inference and learning algorithms with
established physical models, such as partial differential
equations. Advances in this complex field of research require a
concerted effort from many disciplines, which we hope to foster at the


From: Pamela Bye [log in to unmask]
Date: June 14, 2019
Subject: Inverse Problems from Theory to Application, UK, Sep 2019

2nd IMA Conference On Inverse Problems From Theory To Application 4-6
September 2019, University College London, Gower Street, London, WC1E

An inverse problem refers to a situation where the quantity of
interest cannot be measured directly, but only through an action of a
nontrivial operator of which it is a parameter. The corresponding
operator, also called forward operator, stems from a physical
application modelling.  Prominent examples include: Radon and Fourier
transforms for X-ray CT and MRI, respectively or partial differential
equations e.g. EIT or DOT.  The prevalent characteristics of inverse
problems is their ill-posedness i.e. lack of uniqueness and/or
stability of the solution. This situation is aggravated by the
physical limitations of the measurement acquisition such as noise or
incompleteness of the measurements. Inverse problems are ubiquitous in
applications from bio-medical, science and engineering to security
screening and industrial process monitoring. The challenges span from
the analysis to efficient numerical solution.  This conference will
bring together mathematicians and statisticians, working on
theoretical and numerical aspects of inverse problems, as well as
engineers, physicists and other scientists, working on challenging
inverse problem applications.  We welcome industrial representatives,
doctoral students, early career and established academics working in
this field to attend.

Topic list: Imaging; Inverse problems in partial differential
equations (Memorial Lecture for Slava Kurylev) Model and data driven
methods for inverse problems; Optimization and statistical
learning; Statistical inverse problems.

Call for Papers - Papers will be accepted for the conference based on
a 100 word abstract for oral or poster presentation. We welcome
abstracts to be submitted by 30 June via Please
indicate whether your title is intended for oral "presentation" or
"poster" presentation. Please send your abstracts in plain text format
(no equations).

Registration is now open via

For further information about this Conference, please visit:


From: Jurjen Duintjer Tebbens [log in to unmask]
Date: June 16, 2019
Subject: Mathematics Meet Pharmacy, Czech Republic, Sep 2019

We are very happy to invite you to the workshop Mathematics meet
pharmacy, which will take place from 23-24 September 2019 at the
Faculty of Pharmacy, Charles University, Hradec Kralove, Czech

The workshop is targeted at both mathematicians and scientists from
pharmaceutical or related health sciences, including students, with
the main goals being to inform the latter on the the existence of
novel mathematical models useful for their research and to inform
mathematicians about the rich variety of mathematical problems arising
in pharmacy-related scientific fields.

The interdisciplinary workshop will consist of both tutorial/invited
lectures and contributed presentations and there is no registration
fee.  For the website of the workshop, including a list of workshop
themes, see
You can register before 30 June 2019 at:
Applications are being accepted for participation, with the
possibility of a presentation on the application form.

In case you have additional questions, please feel free to contact us
at: [log in to unmask]


From: Dimitri Breda [log in to unmask]
Date: June 14, 2019
Subject: Controlling Delayed Dynamics, Italy, Nov 2019

It is a pleasure to announce the advanced school

Please, feel free to circulate among collaborators and students.


From: Daniel Szyld [log in to unmask]
Date: June 16, 2019
Subject: Mid-Atlantic NA-Day, USA, Nov 2019

The Mid-Atlantic NA Day 2019 will take place at Temple University,
Philadelphia on Friday 15 November 2019.

The purpose of this one-day meeting is to provide a forum for Graduate
Students and Postdoctoral Fellows, i.e., researchers and practitioners
at the very beginning of their careers, from the Mid-Atlantic region,
to exchange ideas in numerical analysis, scientific computing and
related application areas.  More established scientists are encouraged
to attend as well.  Talks start at 10 AM to facilitate same-day

Keynote speaker: Daniela Calvetti, Case Western Reserve University
"The Unreasonable Effectiveness of Numerical Linear Algebra in
Bayesian Inverse Problems"

Abstract submission deadline is 21 October 2017.  There will be no
registration fee, but we ask participants to please register.

Submissions, registration, and more at:

Questions? write to us at [log in to unmask]

Benjamin Seibold and Daniel Szyld


From: Felix Kwok [log in to unmask]
Date: June 12, 2019
Subject: Domain Decomposition Methods, Hong Kong, China, Dec 2019

DD26: deadline extended, registration now open.

We are pleased to announce that registration is now open for the 26th
International Conference on Domain Decomposition Methods (DD26), to be
held at the Chinese University of Hong Kong (CUHK) from December 2 to
6, 2019.  The purpose of the conference is to bring together
mathematicians, computational scientists and engineers who work in the
main themes of Domain Decomposition, including theoretical,
algorithmic and implementation aspects of domain decomposition
methods, solvers for multiphysics problems, parallel-in-time methods,
multigrid and multilevel methods, fast solvers and preconditioning,
and applications of such methods in physics and engineering.

Participants may now register at the URL

The early registration deadline is August 31, 2019. Please note that
the visa requirements are different for Hong Kong and mainland China;
in particular, nationals of about 170 countries and territories may
visit Hong Kong without a visa. For more information on visa
requirements and accommodation options, please visit the conference
website at, or e-mail us at
[log in to unmask]

We are also inviting proposals for minisymposia that fit the theme of
domain decomposition. Proposals should be in the form of a plain text
e-mail to [log in to unmask] Please provide a title, a short
description of the subject matter, and a list of speakers for the
minisymposium. Minisymposia may span one or more sessions, with each
session consisting of four 25-minute talks, with an additional 5
minutes after each talk for questions. Deadline (extended): June 30, 2019.


From: Markus Melenk [log in to unmask]
Date: June 13, 2019
Subject: ICOSAHOM 2020, Austria, Jul 2020

The International Conference on Spectral and High Order Methods
(ICOSAHOM) will take place at TU Wien in Vienna, Austria, July 6-10,

minisymposium proposals are invited by October 4, 2019 Abstract
submission deadline is January 31, 2020 For more information, please

The purpose of ICOSAHOM conference series is to bring together
researchers and practitioners with an interest in the theoretical,
computational, and applied aspects of high-order and spectral methods
for the solution of PDEs.

Invited speakers are:
- Michael Dumbser (Trento)
- Virginie Ehrlacher (Paris)
- Alexandre Ern (Paris)
- Per-Gunnar Martinsson (Austin)
- Siddhartha Mishra (Zurich)
- Anna-Karin Tornberg (Stockholm)
- Marco Verani (Milano)
- Chuanju Xu (Xiamen)


From: Sivaguru S. Sritharan [log in to unmask]
Date: June 10, 2019
Subject: Faculty Positions, Computational Sciences, All Levels

M. S. Ramaiah University of Applied Sciences (RUAS)is a young private
university with a vision to be a leading university in Asia with
global partnerships and innovative curricula. RUAS has several faculty
positions at all levels in subject areas ranging from computational
sciences, machine learning and artificial intelligence, computational
chemistry, hypersonics, plasma-MHD simulation, high fidelity
simulation of fluid and aerodynamics, bio-fluid dynamics including
simulation and modeling of blood flow, etc. Interested applications
are invited to send your CV with complete list of publications and
references to [log in to unmask] Some of the positions are
advertised in however if the
applicants expertise fit the general areas describe above then he/she
is strongly encouraged to send in the applications. Excellent
compensations will be offered. RUAS is located in Bangalore which is
one of the technological hubs of Asia and provides an enormous array
of opportunities.


From: Albert-Jan Yzelman [log in to unmask]
Date: June 12, 2019
Subject: Research Position, Software for Complex Combinatorial Problems

Applications are invited for a new permanent research position at
Huawei's Research Center in Paris. The position will be filled either
by an early-career researcher with high potential (minimum PhD plus 4
years research experience) or by a mid-career researcher currently in
a university position or at a corporate research center (e.g. PhD plus
10 years research experience). The successful applicant will join a
new research team in Paris focused on fundamental long-term research
on next-generation algorithms, software and architectures.  In many
areas this involves both theoretical computer science and practical
software and system development.

The successful applicant will join a new research team in Paris
focused on fundamental long-term research on next-generation
algorithms, software and architectures. In many areas this involves
both theoretical computer science and practical software and system
development. This new long-term research team is led by Bill McColl,
CTO for software research, and comprises members with deep experience
in algorithm design and analysis, computational complexity, machine
learning, graph computing, tensor computations, parallel programming
models, parallel cost modelling, parallel software systems and tools,
constraint programming, declarative computing, domain specific
languages, AI, HPC, scientific computing.

While the specific area for this new long-term research position is
open, candidates with interests and experience in research areas such
as design and analysis of efficient scalable combinatorial algorithms,
theories and tools for complex problem solving, or algorithmic aspects
of declarative computing and software automation, would all be a good
fit, as we grow this new team.

For more information, please see


From: Albert-Jan Yzelman [log in to unmask]
Date: June 12, 2019
Subject: Research position, Algorithms and Software for Graph and Tensor Computing

Applications are invited for a new permanent research position at
Huawei's Paris Research Center. The candidate will join a highly
experienced research team in the fields of mathematics and computer
science led by Bill McColl, CTO for software research, and Albert-Jan
Yzelman who has extensive experience in parallel graph and tensor
computing. For this position, the candidate will focus on the design
of new highly efficient parallel algorithms for multi-linear algebra
and (hyper-)graph algorithms that we expect to form the backbone of
future analytics, machine learning (ML), and AI tasks.

Our team will span aspects ranging from algorithm theory, to help
prove the optimality of our algorithmic designs, to framework
prototypes in which such algorithms may be realized. Your job may
include discovering new lower bounds on relevant classes of
algorithms, finding new parallel algorithms that attain such lower
bounds, or leading research efforts resulting in new insights and
methodologies that greatly enhance software productivity, software
efficiency, and/or the value one may extract from analytics, ML, and AI.

The current vacancy is a senior position, requires a PhD degree in
Mathematics or Computer Science, and at least 9 years experience in
R&D roles, either at universities, research centers, or major
international companies. Creativity and excellent communication
ability in English are key. High potential yet less experienced
candidates with excellent affinity with multiple of the above fields
may be considered for an early-career position.

For more information, please see


From: Chao Yang [log in to unmask]
Date: June 14, 2019
Subject: Postdoc Position, Lawrence Berkeley National Laboratory

The Scalable Solvers Group in the Computational Research Division at
the Lawrence Berkeley National Laboratory (LBNL) has a Computational
Science Postdoctoral Scholar opening in the area of eigenvalue
computation for quantum many-body problems. You will participate in
research activities related to computational mathematics for solving
large-scale eigenvalue problems that arise in quantum many- body
problems relevant to DOE and LBNL missions.

What You Will Do: Develop efficient algorithms for solving nuclear
no-core shell (truncated configuration interaction) models.  Develop
numerical algorithms for accelerating hybrid functional based
Kohn-Sham density functional theory electronic structure calculations.
Develop high performance software tools to accelerate the solution of
quantum many-body problems.

Additional Responsibilities as needed: Develop efficient algorithms
for linear response eigenvalue calculations.  Analyze algorithmic
complexity of new computational approaches.  Implementation of new and
existing algorithms on distributed memory high performance platforms
with GPUs.

What Is Required: PhD in Mathematics, Computer Science, Computational
Science or Engineering within the last 3 years, with a strong
background in computational chemistry, computational physics or
materials science.  Knowledge of quantum many-body problems and
various approximation models (Hartree-Fock, configuration interaction,
coupled cluster, density functional theory, density matrix
renormalization group/tensor networks.)  Knowledge of linear algebra
and multi-linear (tensor) algebra, including sparse matrix
computation.  The successful candidate(s) should be able to program
proficiently in a high-level programming language, such as
C++/C/FORTRAN, and should have experience in parallel computing and be
able to use MPI and OpenMP.  Excellent communication skills.

Additional Desired Qualifications: The candidate(s) also should have
some knowledge of performance optimization for scientific codes.
Knowledge and experience with machine learning techniques or quantum
computing related to quantum many body problems is a plus.

Application can be submitted at


From: Sarah Dance [log in to unmask]
Date: June 10, 2019
Subject: Postdoc Position, Machine Learning, Univ of Reading

PDRA in Machine Learning for High Impact Weather and Flood Prediction

The University of Reading invites applications for a postdoctoral
research assistant to develop and evaluate machine learning techniques
for processing observations of weather and flooding from datasets of
opportunity, such as river cameras.  The goal of the project is to use
Data Science tools and techniques to create a step-change in skill for
numerical predictions of urban natural hazards. The research
undertaken by the post holder will underpin quantitative use of urban
observation data from diverse sources such as citizen science,
crowdsourcing and internet of things. The successful candidate will be
based at the University of Reading, Department of Meteorology but with
close contact with colleagues in Computer Science.

Closing date for applications: 19 July 2019

For more information and to apply, see


From: José Mário Martinez [log in to unmask]
Date: June 13, 2019
Subject: Postdoc Position, Mathematics, Univ of Campinas, Brazil

The Center for Research in Mathematical Sciences Applied to Industry
(CEPID CeMEAI) at University of Sao Paulo opens a post-doctoral
research position in "Geometric Algebra applied to Molecular
Geometry". The selected candidate will work at the Institute of
Mathematics, Statistics and Scientific Computing (IMECC - UNICAMP),
Campinas, SP/Brazil.  Sao Paulo Research Foundation provides the
financial support according to Financial support
can also be provided to cover transportation expenses as to the move
to Campinas - 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: Conformal Geometric Algebra for NMR Protein Structure
Determination Supervisor: Jose Mario Martinez Perez

Description: The calculation of the 3D structure of a protein
molecule, using distances between nearby atoms from Nuclear Magnetic
Resonance (NMR) experiments, is a fundamental problem in computational
biology. The problem is NP-hard, known in the literature by the
Molecular Distance Geometry Problem (MDGP). The problem can be
described using a graph, where each vertex is related to an atom of
the protein and when the distance is known between two atoms, we
define an edge between the respective vertices, with weight given by
the distance value. To solve the MDGP is to obtain an immersion of the
graph in the 3D space, in such a way that the calculated Euclidean
distances between pairs of atoms are equal to the weights of the
corresponding edges. Considering that the distances of the NMR
experiments are precise values, there is a combinatorial approach that
allows the problem search space to be represented by a binary tree,
where an exact Branch & Prune (BP) method is defined to explore the
tree for solutions. The first attempt to generalize these results in
order to include the uncertainties of the experimental data (with the
distances being represented by "interval" values), was to consider
samples at the associated intervals. This idea made the BP algorithm a
heuristic, since it can no longer be guaranteed that a solution will
be found. Refined samples exponentially increase the search space (the
associated tree is no longer binary), and even then, the solution can
be "lost" if the correct distance is between the values selected by
the sampling process. To maintain the properties of the combinatorial
approach and at the same time to consider the interval distances of
the experimental data, we are proposing to represent the protein
molecule in a space of 5 dimensions (Conformal Space), using a
language more powerful than Linear Algebra: Geometric Algebra. The
Conformal Model can be seen as an extension of the Projective Model,
which uses homogeneous coordinates (4 dimensions), widely used in
computational geometry problems. It is desirable that the candidate
should be prepared to work in a multidisciplinary research group,
since the real data will be collected from NMR labs.  The research
will be led jointly by Prof. Carlile Lavor.  Requirements: Applicants
should have PhD in Applied Mathematics with some experience with the
softwares Mathematica and Gaalop.  Candidates must have got their PhD
in the last 5 years.  Application: please send your application before
July 5th, 2019 to Prof.  Carlile Lavor ([log in to unmask]),
indicating "post-doctoral application" in the subject
line. Applications should include curriculum vitae, statement of
research interests and two contact information for recommendation
letters (only PDF files).  Contract Condition: grant from FAPESP under
the Research, Innovation and Dissemination Centers (RIDC-CeMEAI)


From: Marco De Angelis [log in to unmask]
Date: June 10, 2019
Subject: Postdoc Position, Uncertainty in digital twin engineering, Univ of Liverpool

Unique opportunity to study Uncertainty in digital twin engineering
and collaborate with a team of researchers, including: physicists,
engineers, statisticians, and software engineers.  This position is
for quantitative enthusiasts, who want to know more about uncertainty
and risk in engineering.  The successful candidate will be based at
the heart of the Liverpool university campus, next to the university's
sport centre and main facilities (pubs, restaurants, etc.), and will
have plenty of time to study and collaborate in a relaxed,
competitive, and most importantly fun environment.

The opportunity is fully-funded by EPSRC and the School of Engineering
of the University of Liverpool.

Detailed information here:


From: J. Lu [log in to unmask]
Date: June 11, 2019
Subject: Postdoc Positions, Computer Vision/Optimization/Inv Problems, SZU

Postdoc Positions in Shenzhen University, China
Location: Shenzhen, China
Job Type: Full-Time
Duration: 2 years
Number of Position: 4 Positions
Salary: about 380,000 RMB (55,000 US dollars) per year
Closing Date: Open Until Filled

Description: We are looking for Postdoctoral Researchers in
Image/Video Processing/Analysis,Mathematical Imaging, Computer Vision,
Optimization, Inverse Problems, Wavelet analysis, etc.

We have no teaching tasks and check in / check out policy for
Postdoctoral Researchers.

- Prof. Jian Lu (Shenzhen Key Laboratory of Advanced Machine Learning
  and Applications, Shenzhen University)
- Prof. Charles Chui (Editors-in-Chief of ACHA)

Those who are interested please send their C.V. to Prof. Dr. Jian Lu,
e-mail: [log in to unmask]; [log in to unmask]


From: Valeriya Naumova [log in to unmask]
Date: June 11, 2019
Subject: PhD Position, Geometric Deep Learning Simula-UCSD-UiO PhD Program

A PhD position offered as part of SUURPh PhD program
programme) between Simula, the University of Oslo (UiO), and the
University of California, San Diego (UCSD).

The candidate will develop novel theoretically-grounded methods for
processing of non-Euclidean geometric data, aka Geometric Deep
Learning, with applications in medical imaging and sensor data for
brain activity classification.  The successful candidate must have
strong mathematical and computational skills.

Most research activities will be carried out at the Machine
Intelligence Department, Simula, with regular and long-term visits to
the Department of Mathematics / Data Science Center at UCSD.

Further information can be obtained here:

Closing application date: 01 July 2019. The position will start
October 2019.


From: Michael Feischl [log in to unmask]
Date: June 13, 2019
Subject: PhD Position, Maxwell-LLG Equations

The Institute of Analysis and Scientific Computing, E101, at the TU
Wien, is offering a part-time position (30 h/week) for a pre-doc
university assistant for 4 years.  The Monthly Minimum salary is
currently EUR 2.148,40 (14x per year).  Prior experience may result in
higher salary.

The successful candidate will work on the project "Theory and Numerics
of Maxwell-LLG equations" within the CRC "Wave Phenomena" in a
collaboration between TU Wien, University of Tuebingen, and KIT

The PhD candidate can benefit from the collaboration between the three
universities through workshops, research stays, and courses. The
participation on international scientific conferences and the
presentation of research results is part of the position. The
candidate will be part of a big network of researchers on all levels
(PhD candidates, post-docs, professors) working in the CRC.

For more information, visit


From: Christian Gerhards [log in to unmask]
Date: June 16, 2019
Subject: PhD Position, Multiscale Analysis of Potential Fields, TU Bergakademie Freiberg

Applications are invited for a three year PhD position within the
Geomathematics Group at TU Bergakademie Freiberg, Germany.

The position is embedded in the SYSEXPL project, which investigates
the use of potential field methods in geothermal exploration. In
particular, the candidate shall develop multiscale methods to detect
regions where Poisson's theorem for gravitational and magnetic
potential fields holds true. Further information on the position and
the Geomathematics Group can be found at https://tu-

Applicants should hold a master's degree (or equivalent) in
mathematics or a closely related field with above-average
grade. Inquiries can be sent to
[log in to unmask]


From: Dominik Göddeke [log in to unmask]
Date: June 11, 2019
Subject: PhD Positions, Simulation Technology, Univ of Stuttgart

The Cluster of Excellence "Data-Integrated Simulation Science" (EXC
2075) is an interdisciplinary research center with more than 200
scientists performing research toward a common goal: We target a new
class of modeling and computational methods based on available data
from various sources, in order to take the usability, precision and
reliability of simulations to a new level.

In the current funding round, open positions are available in the
following areas: Data-Integrated Models and Methods for Multiphase
Fluid Dynamics; In Silico Models of Coupled Biological Systems;
Data-Integrated Model Reduction for Particles and Continua;
Data-Integrated Control Systems Design with Guarantees; On-the-fly
Model Modification, Error Control, and Simulation Adaptivity; Machine
Learning for Simulation; Adaptive Simulation and Interaction.

More details, including project descriptions and application
requirements and procedures, can be found here: More information
about the SimTech cluster of Excellence is available at:

The University of Stuttgart is an equal opportunity employer.
Applications from women are strongly encouraged. Severely challenged
persons will be given preference in case of equal
qualifications. Selection is competitive, and funding is based on
employment contracts subject to the tariff rules of the State of
Baden-Wurttemberg (TVL E13).


From: Attila Tanács [log in to unmask]
Date: June 14, 2019
Subject: Contents, Acta Cybernetica, 24 (1)

Special Issue of the 11th Conference of PhD Students in
Computer Science

1) Preface

2) Towards a Classification to Facilitate the Design of
Domain-Specific Visual Languages

3) Operations on Signed Distance Functions

4) Multi Party Computation Motivated by the Birthday Problem

5) Benchmarking Graph Database Backends: What Works Well with

6) Keeping P4 Switches Fast and Fault-free through Automatic

7) Multi-Cloud Management Strategies for Simulating IoT Applications

8) Different Types of Search Algorithms for Rough Sets

9) LZ based Compression Benchmark on PE Files

10) A Preparation Guide for Java Call Graph Comparison

11) Combining Common Sense Rules and Machine Learning to Understand
Object Manipulation


From: Roman Chapko [log in to unmask]
Date: June 14, 2019
Subject: Contents, Journal of Numerical and Applied Mathematics, 130 (1)

The new issue Journal of Numerical and Applied Mathematics, 2019, Vol.
130 (1) (Ukraine) is now online:


Ivan Gavrilyuk - 70

Chapko R.S., Ivanyshyn Yaman O.M., Vavrychuk V.G., On the non-linear
integral equation method for the reconstruction of an inclusion in the
elastic body

Fritzsche B., Kirstein B., Madler C., Scheithauer M., The system of
Potapov's fundamental matrix inequalities associated with a matricial
Stieltjes type power moment problem

Gavrilyuk I., Makarov V., The classical orthogonal polynomials in
resonant equations

Pratsiovytyi M.V., Makarchuk O.P., Chuikov A.S., Approximation and
estimates in the periodic representation of real numbers of the closed
interval [0,5;1] by a2-continued fractions

Savula Ya.H., Turchyn Y.I., Replacements in finite element method for
the problem of advection-diffusion-reaction

Tkachenko E.V., Timokha A.N., On acoustic equilibria


From: David G. Yu [log in to unmask]
Date: June 11, 2019
Subject: Contents, Statistics, Optimization and Information Computing, 7 (2)

Table of Contents, SOIC, Vol 7, No 2 (2019)

This issue is available at

On Mean Field Games with Common Noise based on Stable-Like
Vassili N. Kolokoltsov, Marianna Troeva

Performance of Some Confidence Intervals for Estimating the
Population Coefficient of Variation under both Symmetric and Skewed
Moustafa Omar Ahmed Abu-Shawiesh, Hayriye Esra Akyuz, BM Golam

A New Two-Parameter Lifetime Distribution: Properties, Applications
and Different Method of Estimations
Morad Alizadeh, Mahdi Emadi,    Mahdi Doostparast

Stochastic Models to Estimate Population Dynamics
Saba Infante, Luis Sanchez, Aracelis Hernandez

Efficient Online Portfolio Selection with Heuristic AI Algorithm
Amril Nazir

PSO+K-means Algorithm for Anomaly Detection in Big Data
Rasim M. Alguliyev, Ramiz M. Aliguliyev,Fargana J. Abdullayeva

Some Confidence Regions for Traffic Intensity Vector, Suresh Bajirao
Pathare, Vinayak K. Gedam

Properties of non-parametric Stute estimators, Didier Alain NJAMEN

Optimality of Reinsurance Treaties under a Mean - Ruin Probability
Criterion, Abderrahim EL ATTAR, Mostafa EL HACHLOUFI, Zine El Abidine

Viable Solutions for a Class of Delay Evolution Problems, Moufida
Amiour, Mustapha Fateh Yarou

Bi-Level Multi-Objective Stochastic Linear Fractional Programming with
General form of Distribution, Haneefa Kausar, Ahmad Yusuf Adhami

Optimal Control of the Minimal Time Crisis Problem Type by Non- Smooth
Analysis Tools, Abdeldjabar Bourega, Rahma Sahraoui

An Adaptive Image Registration Technique to Remove Atmospheric
Turbulence, Akshay Patel, Dippal Israni, Nerella Arun Mani Kumar,
Chintan Bhatt

Solving Fractional Variational Problem Via an Orthonormal Functio,n
Akram kheirabadi, Asadollah Mahmoudzadeh Vaziri, Sohrab Effati

An Improved Segmentation Approach for Skin Lesion Classification,
Youssef Filali, Sabri Abdelouahed, Abdellah Aarab

Hypercube Based Genetic Algorithm for Efficient VM Migration for
Energy Reduction in Cloud Computing, Navneet Singh, Vijay Dhir

An Analysis of Image Forgery Detection Techniques, Chandan deep Kaur,
Navdeep Kanwal

Improved View Selection Algorithm Using SOM and 0/1 Knapsack, Reyhaneh
Sabbagh Gol, Negin Daneshpour

Variable Selection in Count Data Regression Model based on Firefly
Algorithm, Zakariya Algamal

End of Digest

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