Duties: The primary focus of this project involves both theoretical and applied work in optimal design (design of experiments) and Gaussian processes, with a specific application in epidemiology
Requirements: MSc in mathematics, statistics, computer science, biostatistics, or physics (need not be finished in the time of the application); Some experience in spatial statistics, or numerical linear algebra

Duties: The Department of Mathematics at the University of Rochester invites applications for several non-tenure track Visiting Assistant Professor positions for new or recent PhDs. The positions are for two years, renewable for a third upon satisfactory performance, and carry a 2-2 annual teaching load. Areas represented by the department, including (1) algebraic topology, (2) analysis, (3) combinatorics, (4) differential geometry and global analysis, (5) number theory, and (6) probability, will be preferred
Requirements: Qualifications include a PhD in mathematics, strong evidence of excellence in the teaching of undergraduates, and outstanding promise in research

Duties: As a Deep Learning Scientist, you will design high-performance, state-of-the-art, hybrid architectures for image-based classification, segmentation, labeling, and object detection. This position requires strong theoretical foundations, excellent engineering skills, and sound scientific method. Candidates must have broad and deep proficiency in the foundations of machine learning, CNNs, image processing and computer vision. Candidates must also be adventurous and enthusiastic about an early startup experience!
Requirements: Strong academic foundations from a competitive university/laboratory (Ph.D. preferred); Fluent with state-of-the-art techniques for image-based machine learning; Substantial experience architecting, training, optimizing and evaluating image-based ConvNets; Practical experience building pixel-based image segmentation/boundary/classification networks; Strong applied math skills in linear algebra and linear & non-linear optimization; Solid scientific method & excellent data analysis skills

Duties: Research in the subject area of the announcement, including the development of deep neural networks for the analysis of medical data within ongoing research projects. Teaching at the undergraduate, advanced, and doctoral levels (up to 20% of full-time). Supervision doctoral students and master thesis work. Assisting in seeking external research funding. Collaboration with industry and society within ongoing research projects. Administrative tasks related to the above responsibilities are included. Opportunities for participation in higher education pedagogical competence development will be provided
Requirements: You have a doctoral degree in mathematics; You have excellent proficiency in English, both spoken and written; You have extensive experience in research involving the application of machine learning methods and deep neural networks to medical image data; You have documented experience in collaboration with physicians or other researchers in medicine or with clinical staff; Experience in supervising thesis projects and doctoral students; You have significant experience with development environments for deep neural networks such as TensorFlow, Keras, PyTorch, or similar

Duties: The School embodies a broad range of research interests in the areas of applied mathematics, pure mathematics, statistics, and data science. It has particular research strengths in Algebra, Analysis, Number Theory, Bayesian and Monte Carlo Methods, Biomathematics, Biostatistics and Ecology, Combinatorics, Computational Mathematics, Data Science, Dynamical Systems and Integrability, Finance and Risk Analysis, Fractional Calculus, Functional and Harmonic Analysis, Geometry and Mathematical Physics, Nonparametric Statistics, Ocean and Atmospheric Sciences, Optimisation, Stochastic Analysis, and Stochastic Modelling
Requirements: A PhD in a related discipline, and/or relevant work experience; Proven commitment to proactively keeping up to date with discipline knowledge and developments; Demonstrated ability to undertake high quality academic research and conduct independent research with limited supervision

Duties: Research in the field of the third-cycle studies (PhD studies) in mathematics/applied mathematics, institutional duties, which may include: teaching at undergraduate and advanced level in mathematics/applied mathematics, which may involve teaching at the university's two campus locations, Västerås and Eskilstuna, as well as distance teaching. Supervision and co-supervision at undergraduate and advanced level may also be relevant for the position; administration (e.g. course responsibility or program coordination) and development
Requirements: A degree at an advanced level

Duties: The numerical simulation and visualization of volume deformations constitute an active research domain, characterized by numerous open challenges and opportunities. From materials science to engineering applications such as fluid dynamics and medical imaging, the simulation and visualization of volume deformations are essential. The research group Simulations at UiT is offering a PhD position aimed at delving into these complexities. The PhD project consists of the following key aspects. First, it involves investigating volume representation methods, particularly in materials science. This exploration extends to diverse applications, including the simulation and analysis of composite materials and the dynamics of crack propagation
Requirements: This position requires a master’s degree or equivalent in applied computer science or engineering design, with a completed master’s thesis on a relevant topic and any other requirements. If you are near completion of your master’s degree, you may still apply. In addition, knowledge and experience in the following fields are desirable: Algorithms and programming; Computational geometry; Image registration; Digital volume correlation; Material science CAD/CAM software; Artificial intelligence and machine learning methods

Duties: You will provide support with teaching and also teach high-quality academic classes yourself in Mathematics. Your teaching assignment may include basic mathematics courses as well as more specialized courses in your research domain; You will supervise students and their Bachelor and Master dissertations
Requirements: You hold a Master degree in Mathematics, Physics or Engineering Sciences, or you will have obtained it by the time you start work; You did not yet obtain a PhD in Mathematics; You can demonstrate excellent study results; You have a very good and broad knowledge of analysis, dynamical systems and differential geometry

Duration: temporary       
Workload: 100%
Duties: Public competition for the recruitment of 13 fixed term researcher position, duration 3 years, with possibility of 2-year extension, full-time appointment; Geometria e Algebra; Neurologia; Diagnostica per Immagini; Statistica Medica; Cliniche Chirurgica; Ostetrica Veterinaria; Infrastrutture; Disegno; Filosofia; Psicologia; Diritto; Sociologia
Requirements: Experienced researcher or 4-10 yrs (Post-Doc)

Duties: Bando di selezione n. 21/2023 per il conferimento di n. 1 assegno, tipo A, per lo svolgimento di attività di ricerca
Requirements: Progetto dal titolo "Trasporto Ottimo: nuove sfide tra analisi e geometria/Optimal Transport: new challenges across analysis and geometry"

Duties: The candidate will be expected to work on an independent research program while being encouraged to interact with different research groups. The candidate should contribute to the life of the department, including teaching, seminars, working groups and other research related activities
Requirements: Applicants should be high potential new or recent PhDs, working in derived algebraic geometry

Duties: Carrying out novel research works in one of the following predefined areas; Novel communications technologies for Beyond 5G/6G networks and services; Cellular, UAV, IoT, Tactile Internet, MEC, V2X, D2D, M2M, eMBB, mMTC and URLLC; Machine learning/deep learning techniques and Artificial Intelligence for wireless communications; Reinforcement learning, active learning, transfer learning, federated learning and interpretable/explainable AI; Software defined networking, network virtualization and network slicing for wireless networks; Energy-efficient communication technologies; Energy harvesting, SWIPT, backscatter communications and reconfigurable intelligent surfaces
Requirements: The candidate should possess an M.Sc./M.Eng. Degree in Telecommunication Engineering, signal processing, machine learning or a closely related field in Electronic, Electrical and Computer Engineering. The candidate should have some knowledge and experience in some of the following topics/tools: 5G wireless communications technologies; Wireless Internet of Things (IoT) technologies; Unmanned Aerial Vehicles (UAVs); Resource allocation and optimization; Network virtualization and network slicing

Duties: Subject to availability of funding, the Department will have two openings at the level of Tenure-Track Assistant Professor, with the possibility of appointment at a higher level for exceptional candidates. One of these positions may be named position, the Harold H. Martin chair. The department has identified several priority areas (Algebra & Algebraic Geometry, Computational Applied/Mathematics/Data Science, Discrete Mathematics, Geometry & Topology, Mathematical Analysis, and Number Theory), but outstanding candidates in any area of mathematics may be considered
Requirements: Candidates must have a PhD in mathematics by employment start date and have a strong record of research accomplishments in mathematics as well as effective teaching. Candidate will teach undergraduate and graduate courses in mathematics. The normal teaching load for research-active faculty is 2-1

Duties: We are seeking an outstanding candidate for a Lectureship in broadly interpreted Optimisation for Machine Learning and AI within the School of Mathematical Sciences at the University of Southampton
Requirements: a doctorate and postdoctoral experience in a relevant discipline; ability to obtain peer-reviewed funding; evidence of distinction in research through high-quality publications; ability for undergraduate and postgraduate teaching

Duties: The group offers an attractive working atmosphere and has a long track record of theoretical and experimental collaborations worldwide. Specific research topics include Krylov subspace algorithms, measures of complexity of quantum processes, quantum algorithms for quantum optimization, digital quantum simulation and computation, quantum control, shortcuts to adiabaticity and counter-diabatic driving of isolated and open quantum systems, decoherence, quantum channels, error suppression, and mitigation
Requirements: We are seeking a highly qualified, scientifically ambitious, diligent, and genuinely motivated young scientist willing to pursue a Ph.D. in Quantum Information Theory in a stimulating research-focused environment. An MSc in Physics or an equivalent degree is required to be considered for this position. The candidate needs to possess excellent written and oral English communication skills, a masterful command of the tools of theoretical physics, and an attitude for critical and creative thinking, as demonstrated by transcripts, MSc thesis, and possible prior publications. It is desired that the candidate is familiar with one or more of the following research topics: quantum computation and quantum information theory, quantum algorithms, complexity measures, information geometry, open quantum systems, nonequilibrium quantum phenomena, numerical, analytical, and cloud-computing methods for many-body quantum systems, and mathematical physics