Tips for scientific conference presentations

https://skullsinthestars.com/2024/12/03/my-tips-for-scientific-conference-presentations/

Probability Yardstick infographic

Anyone in the UK intelligence community using the term ‘likely’, for example, should mean a chance of between 55% and 75% (go.nature.com/3vhu5zc).

The best CS courses of the academic year 2023-2024 at Aalto University:

CS-E4580 Programming Parallel Computers, Jukka Suomela
CS-C1000 Introduction to Artificial Intelligence, Arno Solin
CS-E4890 Deep Learning, Alexander Ilin
CS-E4190 Cloud Software and Systems, Mario Di Francesco & Bo Zhao
CS-E4895 Gaussian Processes, Arno Solin

CS-E407517 Special Course in Machine Learning, Data Science and Artificial Intelligence: Seminar on NLP Research, Pekka Marttinen
CS-E5310 ICT Enabled Service Business and Innovation, Kari Hiekkanen
CS-E4910 Software Project 3, Jari Vanhanen & Casper Lassenius
CS-AJ0120 Modern and Emerging Programming Languages: Rust, Arto Hellas
CS-EJ3311 Deep Learning with Python, Alexander Jung

https://www.aalto.fi/en/department-of-computer-science

BSc or MSc degree student, come to work with us on summer 2025. The application form will be open from January 7th to January 31st 2025.

Choose your topic and apply!
https://www.aalto.fi/en/department-of-computer-science/summer-employee-positions-at-the-department-of-computer-science-2025

#Postdoc Research Assistant to join Oxford Martin School Programme on Digital Pandemic Preparedness working with Christl Donnelly & Moritz Kraemer — University of Oxford

https://iddjobs.org/jobs/postdoctoral-research-assistant-to-join-oxford-martin-school-programme-on-digital-pandemic-preparedness-working-with-christl-donnelly-moritz-kraemer

Position for two-year #postdoc with background in computer science interested in working with social scientists/historians to study social evolution through computational lens. Details here:

https://santafe.edu/about/jobs/postdoc-comp-complexity

3-year #PostDoc position centered on the extraction and analysis of relations of societal actors (e.g. politicians, CEOs, ...) from unstructured text data. Feel free to reach out if you want to know more! Deadline: Jan 1st.

https://jobs.uni-graz.at/en/jobs/a122f6d8-06bf-e5a2-6fba-67612e91fb27

Roadmap on machine learning glassy dynamics

Unravelling the connections between microscopic structure, emergent physical properties and slow dynamics has long been a challenge when studying the glass transition. The absence of clear visible structural order in amorphous configurations complicates the identification of the key physical mechanisms underpinning slow dynamics. The difficulty in sampling equilibrated configurations at low temperatures hampers thorough numerical and theoretical investigations. We explore the potential of machine learning (ML) techniques to face these challenges, building on the algorithms that have revolutionized computer vision and image recognition. We present both successful ML applications and open problems for the future, such as transferability and interpretability of ML approaches. To foster a collaborative community effort, we also highlight the ‘GlassBench’ dataset, which provides simulation data and benchmarks for both 2D and 3D glass formers. We compare the performance of emerging ML methodologies, in line with benchmarking practices in image and text recognition. Our goal is to provide guidelines for the development of ML techniques in systems displaying slow dynamics and inspire new directions to improve our theoretical understanding of glassy liquids.

https://www.nature.com/articles/s42254-024-00791-4

Garbage in Garbage out: Impacts of data quality on criminal network intervention

https://arxiv.org/abs/2501.01508

Network Medicine Training Course

https://www.diag.uniroma1.it/network_medicine_training_course

How well prepared are we to rapidly analyse a new influenza pandemic? A brief perspective on analysis conducted for UK government advisory groups during COVID-19

https://epiverse-trace.github.io/posts/covid-analysis/

در مورد جایزه نوبل فیزیک امسال و جان هاپفیلد

https://youtu.be/kXN4OziwI54

Network theory and Bach's music

When you listen to music, does your ability to remember or anticipate the piece tell you anything about its structure? Physicists at the University of Pennsylvania developed a model based on network theory to do just that, describing their work in a February paper published in the journal Physical Review Research. Johann Sebastian Bach's works were an ideal choice given the highly mathematical structure, plus the composer was so prolific, across so many very different kinds of musical compositions—preludes, fugues, chorales, toccatas, concertos, suites, and cantatas—as to allow for useful comparisons.

https://physics.aps.org/articles/v17/21

https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.6.013136

Fractal scaling of trees in art

Leonardo da Vinci famously invented a so-called "rule of trees" as a guide to realistically depicting trees in artistic representations according to their geometric proportions. In essence, if you took all the branches of a given tree, folded them up and compressed them into something resembling a trunk, that trunk would have the same thickness from top to bottom. That rule in turn implies a fractal branching pattern, with a scaling exponent of about 2 describing the proportions between the diameters of nearby boughs and the number of boughs with a given diameter.

https://arxiv.org/abs/2402.13520

Ten research scholarships in complex systems and data science, including computational and digital epidemiology projects

https://sites.google.com/view/lagrange-fellowship

Teaching Assistant Professor in Social Data Science, University of Copenhagen

The Teaching Assistant Professor is expected to devote 70 percent of their time to teaching, course coordination and supervision, 10 percent to administration, and 20 percent to professional development, data management, and teaching/research synergies.

https://jobportal.ku.dk/videnskabelige-stillinger/?show=163227

Controlling the low-temperature Ising model using spatiotemporal Markov decision theory

https://arxiv.org/abs/2501.03668

We introduce the spatiotemporal Markov decision process (STMDP), a special type of Markov decision process that models sequential decision-making problems which are not only characterized by temporal, but also by spatial interaction structures. To illustrate the framework, we construct an STMDP inspired by the low-temperature two-dimensional Ising model on a finite, square lattice, evolving according to the Metropolis dynamics. We consider the situation in which an external decision maker aims to drive the system towards the all-plus configuration by flipping spins at specified moments in time. In order to analyze this problem, we construct an auxiliary MDP by means of a reduction of the configuration space to the local minima of the Hamiltonian. Leveraging the convenient form of this auxiliary MDP, we uncover the structure of the optimal policy by solving the Bellman equations in a recursive manner. Finally, we conduct a numerical study on the performance of the optimal policy obtained from the auxiliary MDP in the original Ising STMDP.

Are you an international bachelor student considering doing your Physics MSc in Copenhagen?

The deadline for applying to the MSc programmes at Københavns Universitet - University of Copenhagen is January 15th if you are a non-EU student and March 1st if you are from the EU.

The Physics M.Sc. is fully in English, and we usually have about 50/50 Danish/international students. There are lots of opportunities for specializing, designing your own programme and for working closely with the reseachers!

The specializations are:
👉 Astrophysics
👉 Biophysics
👉 Computational Physics
👉 Earth and Climate Physics
👉 Physics of Complex Systems
👉 Quantum Physics

read more: https://lnkd.in/dyqjqGt3