PhD in mathematics scholarships for International students [complete directory]

Last Updated on

In his blogpost, PhD in mathematics and computational sciences scholarships are added in form of directory. At the start, a little introduction about subjects and scope of PhD is given. After that, the directory of scholarships in the form of the table is given for your consideration.

Scroll
to bottom of page for complete directory of PhD in mathematics scholarships.

Subjects
covered here are:

PhD in Mathematics

PhD in Computational Sciences

PhD in Mathematics

PhD in
mathematics is a challenging program with hard work of coursework, researches,
thesis, seminars and teaching etc. the dissertation is to be prepared for this
program to earn a degree which is always under the supervision of a professor. Generally,
the program is of about three to five years in which different domains will be
our subjects to work on i.e. coding theory, dynamical system, financial
mathematics, set theory and statistics. Mathematical logic, statistical,
mathematical analysis, topography and stochastic method will be the dose of
courses throughout the year.

PhD in mathematics
programs

Mathematics is broad filed linking directly with computer science, machine learning and many other fields involving programming. There are many PhD scholarships for mathematics lovers in the directory of Physics, and computer science. For people searching for PhD scholarships, the following are best schools for their early-stage research career in the field of mathematics:

MIT

Harvard University

Stanford University

Oxford University

University of Cambridge

Princeton university

PhD in Computational
sciences

Computational sciences are
somewhat similar to mathematics except its closer to practical problems.
Mostly, mathematics deals with theoretical aspect of problems encountering in
natural sciences subjects, however, in case of computational sciences,
numerical models are made for that specific problem to actually bring some
solution or data gathering.

Computational sciences are closer
to natural sciences faculties. It works directly in connection with several
faculties making it highly interdisciplinary field.

In case of natural sciences, Computational science PhD focuses on data collection, data analysis, and interpretation of solution. In case of Statistics, computations and symbolic processing are main part of degree. In case of Engineering, computational sciences mainly focus on life and durability of product. It helps in designing and fabricating of new object.

PhD in mathematics scholarships [complete directory]

PHD Title

Pub. Date

Deadline

Eligible Nationality

Country

Subject

Project Description

Scholarship Link

Computational identification of new functional materials combining machine learning and structure prediction

21/06/2020

30/06/2020

All

University of Liverpool, UK

Material science, computer science, applied math, physics, chemistry

The student will learn how to apply and develop machine learning and structure prediction tools to identify new candidate materials which will be synthesised by experimental collaborators within our research team. The student will work closely with computer scientists, inorganic chemists, physicists, and material scientists to develop and apply software tools

Designing efficient search strategies for new material discovery in complex phase and data space

21/06/2020

30/06/2020

All

University of Liverpool, UK

Material science, computer science, applied math, physics, chemistry

this project will explore optimization methods and routines to develop optimal search strategies for new materials in high-dimensional search spaces, beginning with a single batch of data points, and expanding towards multi-batch searches incorporating information gained from previous batches.

Markov chain Monte Carlo methods for Bayesian data assimilation with application to structural health monitoring

21/06/2020

30/06/2020

All

Belgium

Applied mathematics

In this project, the focus will be on the fundamental problems of developing a framework for Bayesian inference for FE model updating relying upon full-field data and imperfect models. We will consider an approach where the data is treated as a genuine field, rather than a vector with a limited number of entries.

Markov chain Monte Carlo methods for Bayesian data assimilation

21/06/2020

30/06/2020

All

Belgium

mathematics, computer science

This project aims at developing micro-macro Markov chain Monte Carlo methods for data assimilation that reduce the computational cost associated with computing the likelihood for high-dimensional processes.

Theory of x-ray and electron spectroscopy

21/06/2020

30/06/2020

All

Sweden

physics, chemistry, applied math

The PhD student will work in a theoretical project to develop methods for x-ray and photoelectron spectroscopy of materials with complex, correlated electronic structure. The methods to be used are based on quantum mechanics, and involve density functional theory and dynamic mean-field theory.

Theory of magnetisation dynamics

21/06/2020

30/06/2020

All

Sweden

physics, chemistry, applied math

The PhD student will work in a theoretical project to develop methods for magnetisation dynamics. The methods to be used are based on quantum mechanics, and involve density functional theory, dynamic mean-field theory and atomistic spin-dynamics simuations.

MARKOV CHAIN MONTE CARLO METHODS FOR BAYESIAN DATA ASSIMILATION WITH APPLICATION TO STRUCTURAL HEALTH MONITORING

21/06/2020

30/06/2020

All

Belgium

Applied math

In this project, the focus will be on the fundamental problems of developing a framework for Bayesian inference for FE model updating relying upon full-field data and imperfect models

Model order reduction methods for fast parameter estimation and updating of digital twins of mechatronic systems.

21/06/2020

12/07/2020

All

Belgium

physics, mathematics, mechanical engineering

This PhD track focuses on the development of model order reduction (MOR) schemes which allow for the transformation of expensive flexible multibody and (nonlinear) finite element models into lower cost (parameterized) counterparts which are sufficiently small and are tuned for inclusion in a parameter estimation framework.

Methods and applications for Bayesian phylodynamic inference

This project focuses on new developments in a popular Bayesian phylogenetic and phylodynamic inference framework (BEAST: https://github.com/beast-dev/beast-mcmc) and its applications to important evolutionary problems, with a particular focus on infectious diseases.

The PhD project focuses on new sustainable logistic concepts to deal with the increasing complexity for logistics within cities. Urbanization leads to increasing pressure on the limited available infrastructure for the movements of people and goods

Visual Analytics for deep image-to-image models in medical imaging

The PhD in this vacancy will propose new visual analytics methods for ML models that are used in the context of medical imaging acquisition. In collaboration with ML researchers, the PhD will aim at providing the research community, industry, and clinical end users with visual analysis strategies to analyze, interpret, and improve their ML models and training data.

PhD in Bioscience engineering

21/06/2020

15/08/2020

All

Sweden

Math, Bioscience, Computer science

The candidate will work in one of the topics of the BIOSTAT unit (extreme value theory, spatial statistics and sampling problems). The development of statistical methods will be considered as well as the application and validation of these methods on real world data.

CONSTITUTIVE MODELING OF DISLOCATION–SOLUTE INTERACTIONS

21/06/2020

15/07/2020

All

Belgium

Computational materials science, Mathematics

The aim of this Ph.D. project is the development and implementation of a continuum-scale constitutive model for dislocation–solute interactions. To this end, the temperature-dependent interaction of impurity atoms and dislocations will be first studied by means of computer simulations at the scale of individual defects.

The vision is to provide a framework and tool that generates efficient language run times from declarative and verifiable language definitions. The goal of the Ph.D. project is to contribute to this vision.

We are seeking a PhD student to join the Spoofax team to further develop the theory and application of scope graphs and its application in static semantics specification and type checking.

PhD Material Design Under Uncertainty with Bayesian Deep Learning

This position aims at fundamental developments of machine learning methods to design new materials under uncertain conditions. Materials Science sits between fundamental- and applied sciences because a new material needs to consider the entire process-structure-property chain.

Doctoral Student in Computer Science Focused on SAT Solving and Combinatorial Optimization

21/06/2020

06/07/2020

All

Lund Univerity, Sweden

Computer Science and Engineeirng, Electrical Engineering, Physics, Mathematics

The PhD student will be working in the research group of Jakob Nordström. Much of the activities of this research group revolve around the themes of efficient algorithms for satisfiability in propositional logic (SAT solving) and lower bounds on the efficiency of methods for reasoning about SAT (proof complexity).

Two PhD student positions in Semi-supervised Learning for Medical Image Analysis

21/06/2020

09/08/2020

All

Chalmers University of Technology, Sweden

Physics, mathematics or computer science

In this project, we will develop new methods and techniques for SSL and apply it to medically relevant problems where lots of image data is available.

PhD student position in computational mathematics for SPDEs

21/06/2020

09/10/2020

All

Chalmers University of Technology, Sweden

Applied Mathematics

We will recruit one doctoral student in mathematics to work under the supervision of David Cohen on a project related to the numerical analysis of Stochastic Partial Differential Equations (SPDEs)

PhD Position at Department of Data analysis and mathematical modelling

The research group is part of the Department of Data analysis and Mathematical Modelling and has a broad expertise in the theory and methods of statistical data analysis and its applications in the field of bioscience engineering. The candidate will work in one of the topics of the BIOSTAT unit (extreme value theory, spatial statistics and sampling problems).

MICROPHONES AND ALGORITHMS FOR NON-INVASIVE HUMAN CARDIO-RESPIRATORY MONITORING

21/06/2020

20/07/2020

All

KU Leven Belgium

Computer Sicence and Engineeirng, Physics, Mathematics

We are hiring a PhD candidate to participate in the “Plug ’n Patch” personalized VLAIO ICON project that targets an innovative design methodology for medical patches that include customized sensors such as a skin coupled microphone (stethoscope).

MACHINE LEARNING MODELS FOR INDOOR PERSON MONITORING USING RADAR SIGNALS (PHD)

21/06/2020

20/07/2020

All

KU Leven Belgium

Computer science, physics or mathematics

We are hiring a PhD candidate to participate in the “NextPerception” European H2020-ECSEL project that targets next generation smart perception sensors and distributed intelligence for proactive human monitoring in health, wellbeing, and automotive systems.

HYBRID AI FOR MACHINE LISTENING APPLICATIONS (PHD)

21/06/2020

20/07/2020

All

KU Leven Belgium

Computer science, physics or mathematics

In short in this PhD research DTAI-ADVISE wants to investigate the use of hybrid AI techniques within the field of machine listening and more specifically on two use-cases: indoor human activity monitoring and smart maintenance.

PHD STUDENTS, IN MATHEMATICS, PHYSICS, ASTRONOMY AND COMPUTER SCIENCE ON THE SUBJECT OF UNRAVELLING NEURAL NETWORKS WITH STRUCTURE-PRESERVING COMPUTING (UNRAVEL)

21/06/2020

15/07/2020

All

CWI Germany

Mathematics, physics, astronomy, computer science

The main objective of this project: revealing how neural networks can be made much more effective by incorporating mathematical and physical understanding in their design.

4 Fully-funded PhD positions in Imaging and Data Science in Berlin

21/06/2020

06/07/2020

All

Helmholtz Research Institute

Physics, mathematics, computer science, data science, Biology

PhD candidate in clinical optoacoustics: Imaging vascular physiology and disease (f/m/d

21/06/2020

30/09/2020

All

Technical University of Munich Germany

Mathematics, natural sciences

The project is geared toward clinical applications of hand-held optoacoustic imaging systems (MSOT and RSOM) that deliver label-free imaging and sensing of diverse biological components.

PhD position: HIP Kinases as regulators of cell fate decisions

21/06/2020

14/07/2020

All

Justus-Liebig-Universität Giessen Germany

Mathematics, natural sciences

n this project we will investigate the regulation of kinases belonging to the family of homeodomain-interacting protein kinases (HIPKs). Th