Programs > Brochure
IIP-Max Planck Institute for Dynamics and Self Organization
Goettingen, Germany (Outgoing Program)
|Partner Institution/Organization Homepage:||Click to visit|
|Restrictions:||Princeton applicants only|
|Dept Offering Program:||IIP, International Internship Program (IIP)||Program Type:||Internship|
|Language Prerequisite:||No||Degree Level:||2 First year Ugrad, 3 Sophomore, 4 Junior|
|Time Away:||Summer||Housing options:||Student Responsibilty with support from IIP and/or Host Organization|
|Program Group:||International Internship Program|
About: The Max Planck Institute for Dynamics and Self-Organization is a research institute for investigations of complex non-equilibrium systems, particularly in physics and biology. It is one of 80 institutes in the Max Planck Society (Max Planck Gesellschaft). The institute has four departments conducting research in the following areas: nonlinear dynamics, fluid dynamics, pattern formation, biocomplexity, and dynamics of complex fluids.
Intern Responsibilities: IIP interns will work on tasks related to the following experimental and theoretical projects at the Institute.
- Control of pattern formation in Dictyostelium discoideum cells: A classic example of self-generated patterns in nature is found in the social amobae Dictyostelium discoideum. When starved, millions of individual cells signal each other with the signaling molecule cyclic adenosine monophosphate (cAMP). cAMP waves in the form of spiral or target patterns propagate in cell populations and direct aggregation of individual cells to form centimeter-scale Voronoi domains and eventually multicellular fruiting bodies. In this study, the laboratory controls the shape of Voronoi domains by introducing periodic geometrical obstacles with different size and periodicity in the system. Observations are made that the obstacles act as aggregation centers and the periodic arrangement of the obstacles is reflected directly in the corresponding Voronoi domains.
- Cell migration in Electric Field - Cells have the ability to detect continuous current electric fields (EFs) and respond to them with a directed migratory movement. Dictyostelium discoideum (D.d.) cells, a key model organism for the study of eukaryotic chemotaxis, orient and migrate toward the cathode under the influence of an EF. The underlying sensing mechanism and whether it is shared by the chemotactic response pathway remains unknown. Observations are made that besides triggering a directional bias EF influences the cellular kinematics by accelerating the movement of cells along their path. Through the analysis of the PI3K and Phg2 distribution in the cytosol and of the cellular adherence to the substrate we aim at elucidating whereas this speed up effect in the electric field is due to either a molecular signalling or the interaction with the substrate.
- Stochastic description of Chemotaxis - Chemotaxis, the directed motion of a cell toward a chemical source, plays a key role in many essential biological processes. The directional motion is described as the interplay between deterministic and stochastic contributions based on Langevin equation. The functional form of this equation is directly extracted from experimental data by angle-resolved conditional averages. It contains quadratic deterministic damping and multiplicative noise. The IIP intern will use this lab's approach, which captures the dynamics of chemotactic cells, and will quantify differences and similarities of different amoeba and characterize the heterogeneity within a population of migrating cells.
- Thermal convection - Thermal convection is fluid flow driven by a thermal gradient. If the thermal driving is strong, the flow is turbulent. Such flows are one of the most efficient heat transport mechanisms and occurs in many industrial and natural systems. We investigate the heat transport and the fluid flow by thermal convection in cylindrical vessels with a hot bottom and a cold top plate. Most investigation assume Boussinesq conditions. That means that the fluid properties are the same at the warm bottom and the cold top plate. While studying such simplified systems is important for a fundamental understanding of the underlying mechanisms, in many industrial and natural convection systems, the Boussinesq conditions are not fulfilled. In example, for industrial cooling systems, supercritical gases are used that have viscosities similar to gases but heat capacities of liquids. Other examples are atmospheric convection or convection in stellar interiors. In this project, the IIP intern would study turbulent thermal convection at strongly non-Boussinesq conditions by using Sulfur-hexafluoride (SF6) above its critical point. The heat transport and the flow field are studied using thermal probes and optical techniques.
- Active Droplet Swimmers in Complex Geometries - This research group studies active liquid crystal droplets and their behavior in well-controlled microfluidic geometries like channels, pillars and grain/sphere packings in 2D and 3D using light and 3D light sheet fluorescence microscopy. The IIP intern will assist in the fabrication of microfluidic PDMS devices, the recording of video microscopy data and their evaluation using existing software packages.
Previous work experiences (in the words of past IIP intern): Intern #1: We had an active grid, which is an array of paddles which are computer controlled to run a certain rms velocities and angles. I programmed these paddles to have certain shapes and statistical properties. Then, using a wind tunnel we measured statistical properties of the resulting turbulent flow through these paddles. Intern #2: I studied energy decay in turbulence by using an active grid and a wind tunnel. The active grid lets us control how we stir up the air in the wind tunnel, and we can measure it's effects on turbulence. In the mornings, I generally worked on coding the active grid, analyzing data, or reading papers. In the afternoons, I took data in the wind tunnel. Intern #3: Basically, I worked with a very specific type of amoeba, called Dictyostelium discoideum, which I took lots of data of. Frequently I injected the ameoba into small chambers, and then I recorded images of the movements of the amoeba for hours. While the data is being taken, I used imageJ and Matlab to look at and analyze data that I've taken from previous days. With this data I tried to determine specific information about the communication and movement of the amoeba. Intern #4: I set up experiments in the morning that run all day. It involved working with Dictyostelium (an amoebae) in a microfluidic channel, and I investigated resonance/phase locking in the system. In the afternoons I did prep work for the experiments and analyzed the data I have collected (using image J and matlab). We had been working on a few different ways to analyze the data and tried some new ideas. Hopefully the work can be complied into a Arnold tongue graph (showing the resonance conditions of the system)...I am learned not only how to work in the lab with Dictyostelium but the data analysis is really interesting. I have tried a few different ways to extract useful/accurate information from the microscopy pictures, it was interesting to talk with my supervisor to evaluate the results and discuss new approaches. Intern #5: My fellow IIP intern and I worked on an experiment to see how movements of tiny paddles in a wind tunnel affect the flow in a wind tunnel. This involved programming the paddles in C++ to move in a variety of correlated configurations, designing experiments/ collecting velocity data in the wind tunnel, and analyzing the data using matlab code. We wrote a paper by the end...One of the goals of the Max Planck Institute is to better understand turbulence. We studied the very important idea of the decay of turbulence over time...I learned a lot about the theory of turbulence and some statistics too. Also I learned a ton of C++, which has been a great way to practice some of the skills I learned in COS217 this spring. Intern #6: We were studying turbulence decay in a wind tunnel, using concepts from classical turbulence theory. We were attempting to induce changes in turbulence using an active grid, composed of 129 paddles mounted to independently controlled servo motors. We implemented a new feature in the control code that allows the experimenter to generate grid movements that are correlated in time, and not just in space. Then, we were working in the experimental hall, running tests on the grid in a wind tunnel and collecting data. In between tests, we ran data processing scripts (coded in MATLAB) and generated correlation functions and energy decay functions. After our data collection phase was finished, we processed the data further, organized it into a presentable form, and wrote reports summarizing our findings and the technical details about our code...I learned experimental methods, new programming skills, and data collection methods. I also learned how to negotiate theoretical issues in light of time, algorithm, and hardware constraints.
View a PowerPoint presentation by a past intern:
Liu, Jessie, Max Planck, Germany.pdf
Max Planck Institute for Dynamics and Self-Organization_Germany_Wei_Nathan.pdf
Max Planck Institute, Germany, Griffin, Kevin.pdf
|Dates / Deadlines:|