Events

Doctoral candidate Sisay Mebre Abie at the Department of Physics, Faculty of Mathematics and Natural Sciences, is defending the thesis 

"Bioimpedance as a tool for monitoring the effect of freezing and thawing of meat"

for the degree of Philosophiae Doctor.

The 71st annual meeting of the Nordic Microscopy Society.

We are delighted to invite you to the EarthFlows June Meeting 2021.

Constructive alignment of learning aims, examination and learning activities is a convincing principle for course design. However, to make a meaningful alignment, we first need to precisely define and understand these aspects in the context of a given course. For instance, if learning aims are to truly guide/define examination and learning activities, we need a rich conception of learning aims that goes well beyond the short, general and typically vague formulations provided on course web pages. As always, devil is in the details. To initiate a discussion, I will show examples of how we have tried to face the challenge of being sufficiently concrete in our approach to constructive alignment in the course IN1000 (a large introductory programming course at UiO).

Friday 21.5, 1415-1500: Tor Ole Odden

Friday 28.5, 0915-1000: Kirsty Dunnett

After having taught computing in a mathematical setting for many years, I have collected a number of observations and hypotheses about how students develop their understanding. In particular I have seen many examples of how computing triggers understanding of mathematical concepts. Some of these are quite standard, eg.  numerical integration as a tool to extend the understanding of the definition of the integral. In this talk I will discuss some fairly obvious examples of this kind, but I will focus on some less obvious examples. Hopefully, this will illustrate that computing can be integrated fruitfully with mathematics in areas far beyond what we do today.

Jay Fineberg (The Hebrew University of Jerusalem): How Friction Starts: Nucleation fronts initiate frictional motion

Stefanos Papanikolaou (National Center for Nuclear Research, Poland): From statistical features to mechanical yielding in digital image correlation and surface strain maps

In the new CompSci MSCA PhD program we will educate 32 PHD-students across the faculty. They will all have a 20 ECTS intensive introduction course in computing and data science. This will open new opportunities to develop PhD-level courses in the spirit of the CS program. I will introduce a discussion of what the contents and level of such courses should be with a particular focus on how Fys4150 and Fys-stk4155 can be adapted to students with diverse computational skills.

Irene Manzella (University of Plymouth): Volcanoes, landslides and tsunamis: a numerical study of the 2019 Stromboli events

Neal Iverson (Iowa State University): A slip law for glaciers

It would be a mistake to assume that students have learned the thing you just presented to them. Formative assessment is thus concerned with informing both the teacher and the student about how much students understand about a topic, and discover any misunderstandings.

Elsa Bayart (ENS de Lyon): Solid friction: heterogeneities and rupture arrest

Jonathan Bamber (University of Bristol): A Bayesian Hierarchical Modelling approach to solve for sea level, global mass movement and solid Earth deformation simultaneously

Ramin Aghababaei (Aarhus University): Micromechanics of surface asperities fracture during sliding contact

Doctoral candidate Fabio Zeiser at the Department of Physics, Faculty of Mathematics and Natural Sciences, is defending the thesis 

"Uncertainty quantification for nuclear level densities and γ-ray strength functions from the Oslo method and beyond"

for the degree of Philosophiae Doctor.

Anne Pluymaker (U Delft): Fluid-limestone interactions: a rock mechanics approach

The seminar will be in Norwegian: "Vi presenterer en modell for kompetanseheving i realfaglig programmering for lærere. Modellen tar for seg opplæring i programmering på fagenes premisser, og vi ser på hvordan en slik modell kan brukes for lærere i høyere utdanning."

Most of you have now spent the last three semesters working on one of the biggest projects of your life so far: your master thesis project. In collaboration with KURT, we want to give you the chance to join a workshop that will give you a space to learn how to create your master thesis.

Åke Fagereng (Cardiff University): Effects of heterogeneity on fault slip behaviour

Suzanne Hangx (Utrecht University): The importance of understanding fluid-rock interactions for geo-energy storage and production: learnings from CO2 storage

Computational thinking are by some defined as the capability to resolve problems algorithmically and logically, including skills related to representing, organizing and identifying patterns in data. This may be seen as leaning in a direction of discrete and observable processes. The Norwegian translation to "algoritmisk tenkning" can be read even clearer in the direction of defining explicit, deterministic instructions to achieve a well understood outcome. At the same time, computational thinking is not only promoted as a means to allow the development of concrete code/algorithms, but also as a way of thinking constructively about phenomena in a variety of fields. And it is clearly not the case that all phenomena in nature and society only involve discrete, directly observed entities - to the contrary, many relations and processes we may be interested in are continuous and probabilistic in their nature, where we have to constructively relate to risks, uncertainties and underlying patterns. An interesting question is whether the ability to devise algorithms to solve well defined problems and the ability to relate constructively to questions in an uncertain world should be seen as two aspects of the same skillset, or as separate skills that are cultivated through separate learning experiences.