IIP Internships in Germany
Max Planck Institute for Dynamics and Self-Organization
Location: Goettingen, Germany
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.
Qualifications: Candidates with interests in physics, biology, math, and natural sciences are encouraged to apply.
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:
Max Planck Institute Intern #1
Max Planck Institute Intern #2
Max Planck Institute Intern #3
Max Planck Institute Intern #4
|For UPDATED information on SUMMER 2017 and TO APPLY, click here: Max Planck Institute|
Max Planck Institute for Ornithology, Department of Collective Behavior
Location: Berlin, Germany
About: The goal of the Max Planck Society for the Advancement of Science is to support excellent fundamental research in the natural, life, and social sciences, as well as arts and humanities. This goal is achieved in more than eighty Max Planck Institutes, each of which focuses on a single area of research. The Institutes of the Max Planck Society are independent and autonomous in the selection and conduct of their research pursuits. Each institute has its own, internally managed, budget, which is supplemented by third-party funds through competitive research grants and collaborations. The Max Planck Institute for Ornithology has four departments: Department of Behavioral Neurobiology, Department of Behavioral Ecology and Evolutionary Genetics, Department of Migration and Immuno-Ecology and Department of Collective Behavior. The Max Planck Department of Collective Behavior consists of three labs which work on a wide range of organisms in both the laboratory and field, including fish, insects, arachnids, mammals and birds. Their department is a highly interdisciplinary environment with a closely integrated experimental and theoretical research program to understand the fundamental principles that underlie collective behavior across levels of biological organization. The systems used are both observable and readily able to be manipulated, and are ideal subjects with which to develop and test mathematical models that predict dynamic group-level properties from the behavior of smaller components. By integrating research at all levels of organization – from the neuro-biological mechanisms of social interaction all the way to movement ecology of social groups of large vertebrates – their research provides unrivaled opportunities to quantify the behavior of individual components within the context of the collective.
Intern Responsibilities: IIP interns will work on one or more of the following projects:
- Project 1 - Collective Sensing: In the natural world, individuals constantly face the challenge of acquiring, interpreting and responding to complex sensory information. Empirical evidence suggests that animals deal with this challenge by living in groups and processing information collectively. While these collective properties are manifested at the group level, they are an outcome of decisions made by individuals. In general, it is unclear how selection on behavioral rules adopted by individuals leads to evolution of group level properties such as collective information processing and distributed sensing. Previous models in collective behavior have been successful in explaining experimental data in a range of contexts and species, including leadership and consensus decision-making in fish and baboons. Even though these models work well predicting group behavior in moderate to large groups, they fail to reliably reproduce behavior in small groups and solitary individuals. This limitation constrains our ability to truly examine benefits of collective information processing and distributed sensing because it prevents comparison across various group sizes.
The IIP intern will be involved in analyzing movement data from lab based recordings of fish in isolation and in varying group sizes and building on top of existing schooling models to account for individual behavior. This more realistic models will then enable comparison across scales from individuals to collectives.
- Project 2 - Neural Network Based Collective Decision-Making: While there are many advantages to living in a group it is also often advantageous to cheat on one’s responsibilities in the group. This free rider problem can lead either to instability in groups, or, to groups never forming in the first place. The team builds simulations that examine the conditions from which stable collective hunting and collective prey evasion emerge from naive random walk-like behavior. Their simulations are inspired by work from DeepMind on deep reinforcement learning.
IIP interns would create learning based simulations, either starting from scratch or building off existing simulations in the lab, that examine how the abilities of individuals and the condition of the environment in which they exist affect the emergence and type of collective behavior in predators and prey. How, for instance, does changing individuals’ range of possible movement actions affect group level behavior? How does adding visual occlusions in the environment (like boulders in nature for instance) affect the learned hunting strategies of predators and how do prey respond?
- Project 3 - Quantitative approaches to the study of animal behavior: When individuals use socially acquired information during search, they are trying to simultaneously reduce their uncertainty about the environment and avoid personal costs by exploiting the efforts of others. However, relying on social information is not always adaptive. While social information may be less expensive to acquire, it is potentially unreliable. In contrast, personal information is more reliable but risky and effortful to obtain. Under conditions of limited time and cognitive resources, how do individuals navigate this trade-off and decide which information to use? To investigate these ideas I run a series of experiments that track human eye movement while humans solve visual search tasks. I hope to understand 1) when and how searchers use social information during complex, difficult search tasks and 2) the effects of social information on search behaviors and performance.
IIP interns would work to help analyze the results of these experiments exploring how humans weigh personal and partner information while solving these problems. How, for instance, does the cognitive difficulty of a task affect how reliant an individual is on those around it? How do people respond to varying levels of noise in their own information vs. the information around them? If the intern is willing to be trained at Princeton in the spring they can also run their own experiments.
- Project 4 - Collective behavior in locust swarms: Understanding how organisms process sensory information in the brain to produce behavior is one of the most exciting scientific problems of the 21st century. More specifically, understanding the sensory and behavioral mechanisms that animals use to successfully migrate long distances is one of the great scientific challenges of our time. Movement in migrating swarms of locusts is driven by cannibalistic interactions where individual movement decisions are made based on the threat of being cannibalized from behind and the motivation to cannibalize others ahead. The behavior of individuals within these marching bands is the result of visual and physical contact between individuals. The lab studies questions related to how sensory information and individual behavior influence the movement dynamics of group migration. Marching behavior in juvenile desert locusts is used as a model system to address two broad questions: 1) How do sensory information networks drive individual decision-making and group-level movement dynamics in migrating animal groups? 2) How do individual differences in behavioral state and group composition influence movement dynamics in migrating animal groups? The team conducts experiments in behavioral arenas that are filmed using multiple synchronized high-resolution 4K video cameras. Using computer vision techniques we measure the movement of individuals while also maintaining individual identities with 2-D bar code tags (similar to QR codes) attached to individuals. The visual fields of individuals are calculated using ray casting algorithms like those used in video game engines. By measuring visual and physical interactions between individuals we can infer the underlying social networks that drive both individual and group-level movement.
IIP interns will help design and conduct experiments and analyze these data using unsupervised machine learning methods to classify behavior of individuals and describe changes in behavioral state across time and context.
- Project 5 - The dynamics of group hunting and collective evasion: One benefit of sociality in prey animals is collective predator detection. For collective detection to occur, information regarding the presence of predators must be transferred from knowledgeable individuals (detectors) to naive individuals (non-detectors). For this project, the lab will use drone-mounted cameras to capture aerial videos of ungulate (hoofed animal) groups in Kenya to study individual and group level vigilance patterns. To observe the process of information transfer, we will present model predators to groups and record their reactions. From these videos, the lab will extract continuous movement and behavioral (head up/head down) data for every member of the group, and calculate distances between individuals. Because of the complex background of these aerial videos, the data can only be extracted from the videos with deep learning based object detection and recognition algorithms. Deep learning models developed by Facebook Artificial Intelligence Research (FAIR) are particularly promising for this project (https://github.com/facebookresearch/multipathnet). Using the data extracted from these videos we can computationally reconstruct visual fields of individuals and, along with 3D habitat models, explicitly consider the information available to each individual and investigate how this information affects individual behavioral decisions. Other people will carry out the actual filming, but the IIP intern can help with every other aspect of this project spending the most time working on what most interests them.
- Project 6 - Revealing the structure of sensory interaction networks in animal groups: The predominant paradigm in the study of animal collectives has been to consider individuals as self-propelled particles which interact via social forces such as local repulsion, and longer-range attraction. This approach fails to consider key aspects of biology for many group-living species such as identity, social status, relatedness and informational status. The social relationships within these groups can change the interactions among individuals and have strong effects on the function of animal groups, yet understanding of social hierarchy in the context of collective behavior is limited.
In this project, the team explores collective decision-making in an organism that forms stable, highly coordinated and socially stratified groups – the damselfish, Dascyllus marginatus. This is a tropical marine species that forms stable size-based social hierarchies of unrelated individuals in close association with branching coral species. I employ multi-camera imaging technology in order to track simultaneously the motion and behavior of each member of D. marginatus groups, in three dimensions, in the field (Red Sea, Israel). Using various stimuli, the team will explore the relationship between individual- and group-behavior in three ecologically relevant contexts: (A) Detection of potential threats (B) Individual and socially-mediated escape manoeuvres and (C) Decision-making regarding emergence. Acquiring data from the videos constitutes a challenging computer vision problem. Interns can be involved in developing programs to automate data acquisition, as well as developing tools to visualize the data in three dimensions.
Qualifications: IIP candidates with interests in mathematics, physics, electrical engineering, computer science, operations research and financial engineering, mechanical and aerospace engineering, economics or ecology and evolutionary biology or related fields are encouraged to apply. Technical programming skills in python, C++ and an interest in machine learning and computer vision would be an asset.
|For UPDATED information on SUMMER 2017 and TO APPLY, click here:
Max Planck Department of Collective Behavior
Max Planck Institute of Quantum Optics
Location: Garching, Germany
About: MPQ is a research facility of the Max Planck Society, dedicated to basic research on the interaction of light and matter under extreme conditions. It consists of several sub divisions (Laser Spectroscopy, Quantum Dynamics, Attosecond and High-Field Physics, Theory, and the division of Quantum Many Body Systems) and several independent research groups, with a total of more than 200 scientists. The stimulating research environment at MPQ results from fruitful collaboration and know-how exchange of the different groups and divisions, making it one of the world-leading research institutions in this field.
Intern Responsibilities: IIP interns will work on one of the following projects:
Projects in Prof. Cirac’s group (Theory): Since 2001 Prof. Dr. J. I. Cirac is Director at the MPQ and head of the Theory division. He has made contributions to quantum many-body physics, information and optics and is an expert in the field of quantum information and quantum computation.
- Project 1: Dissipative quantum systems: The IIP intern will apply the numerical algorithms developed in our division to the study of dissipative quantum systems. In particular, different spin chains may be considered. The tasks may include particularizing the algorithm for the chosen problem, designing and performing the numerical study, and analyzing the results.
- Project 2: Study of topological phases and phase transitions using tensor networks - The IIP intern will apply tensor network algorithms to the study of topological phases and their excitations. This can in particular include models obtained by adding fields to existing models, and the investigation of the topological phase transition between these models. The student will learn basics of topologically ordered phases, as well as the use of tensor network methods, in particular Matrix Product States (MPS) and Projected Entangled Pair States (PEPS). This project will require a combination of analytical and numerical skills.
- Project 3: Computational complexity of physical problems - Computational complexity addresses the difficulty of physical problems. In this project, the student will study how to relate existing complexity results, in particular for the computation of the ground state energy to polynomial accuracy, with physically relevant problems such as the computation of correlation functions, expectation values of local observables, or response functions. This project is very mathematically oriented, as it crucially depends on rigorous error bounds for all approximations used.
Projects in Prof. Bloch’s group (Quantum Many-Body systems): Since 2008, Prof. Immanuel Bloch is Scientific Director of the Quantum Many-Body Systems division at MPQ. With his research, Immanuel Bloch has opened a new and interdisciplinary research field at the interface of quantum physics, quantum information science, atomic- molecular- and condensed matter physics. With the help of ultracold atoms in optical lattices, the vision of physics Nobel prize winner Richard Feynman, i.e. a quantum simulator for studying complex quantum matter, has become reality today.
- Project 1: Setup of diode laser systems for laser cooling & trapping - The IIP interns will learn how to build a diode laser systems including spectroscopy and frequency control that will later be used for laser cooling and trapping of ultracold atoms. The students will learn the basics of frequency control of a laser system, including the control electronics and feedback system. This also includes fundamentals of laser optics and optical modulation techniques.
- Project 2: Light intensity control system - The IIP intern will learn the basics of light detection, and optical modulators to implement a feedback control system for optical power stabilization used in optical dipole traps for ultra cold atoms. Basic signal analysis as well as some electronics techniques will be used to explore quantum mechanical limits in optical power detection and optimal feedback control.
Qualifications: IIP candidates with interests in quantum physics, quantum information, Many-Body Theory,and elementary atomic physics are encouraged to apply. Basic computer programming skills are required. Upper level physics courses are strongly recommended.
|For UPDATED information on SUMMER 2017 and TO APPLY, click here:
Max Planck Institute of Quantum Optics
Location: Munich, Germany
About: ReActive Robotics is a startup company that develops robotics which provide early movement rehabilitation for patients after a neurological injury or an orthopedic surgery. Concretely, ReActive Robotics is building a robot that can attach to a patient’s ICU bed and help him or her to perform crucial rehabilitation. Therapy is brought to the patient rather than transferring the patient onto a separate therapy device: because the patient remains in bed, the device can be deployed as early as 48 hours after injury, directly in the ICU. This very early mobilization (VEM) therapy that has been clinically proven to help patients recover faster and reduce their time in the ICU. Their team works on almost all aspects of product development: from mechanical design and software programming, to business strategy and an extensive quality control regime. IIP interns will have the opportunity to see the product certification process up close, and to have a direct and measurable impact on the company.
Intern Responsibilities: IIP interns will work on one or more of the following three projects:
- Project 1: Automatic Adaption System - Assisting Control Engineers on Implementation
ReActive Robotic's robot guides and assists the patient to perform a step-like walking movement by attaching to their knee through an orthosis and moving their knee along the desired trajectory. The current version of the robot requires the therapist to attach the knee orthosis in the correct position and to measure and input certain patient dimensions (e.g. shin and thigh length). The goal is to automate this process in order to optimize the therapist’s time and allow them to treat more patients. The IIP intern will work with our control engineers to implement an automatic adaptation system that autonomously adjusts our robot’s knee orthosis to the patient’s physiology, and obtains the required measurements. This auto-adaptation system will be designed from scratch and the IIP intern will have the opportunity to influence the approach taken.
- Project 2: Automatic Adaption System - Assisting Hardware Engineers to Complete Initial Mechanical Design
ReActive Robotic's robot guides and assists the patient to perform a step-like walking movement by attaching to their knee through an orthosis and moving their knee along the desired trajectory. The current version of the robot requires the therapist to attach the knee orthosis in the correct position and to measure and input certain patient dimensions (e.g. shin and thigh length). The goal is to automate this process in order to optimize the therapist’s time and allow them to treat more patients. The IIP intern will work with our hardware engineers to complete the initial mechanical design (using CAD) of an automatic adaptation system that autonomously adjusts our robot’s knee orthosis to the patient’s physiology. This auto-adaptation system will be designed from scratch and the IIP intern will have the opportunity to influence the approach taken.
- Project 3: Graphic User Interface
This project consists of developing and improving an existing Graphical User Interface (GUI) used by ICU therapists to perform therapy using the robot. The IIP intern will implement the GUI in consultation with our multidisciplinary software team, balancing usability needs with established safety requirements.
- Project 4: Market Development Research
The IIP intern will work with our CEO to perform market development research for a medical device in the US. ReActive Robotic's current market is Europe and they are working towards obtaining product certification in the EU. The IIP intern will investigate the potential market for our device in the US, identifying where it should be marketed and researching the initial steps required to obtain certification.
Qualifications: German language skills are not required for the job, the work is conducted in English. However, German might be useful for the intern’s social life outside of the lab and during lunch, breaks etc at the lab.
- Project 1 qualifications: IIP candidates with interest in mechanical and aerospace engineering or electrical engineering, as well as, an interest in automatic control are encouraged to apply. Coursework in MAE-433 (Automatic control systems) would be an asset. IIP candidates should also have familiarity with frequency-domain control approaches (PID controllers, transfer functions etc.). Experience in object-oriented programming (ideally C++) would also be an asset.
- Project 2 qualifications: IIP candidates with interest in mechanical and aerospace engineering and specifically mechanical design are encouraged to apply. Experience using a CAD program (such as SolidWorks) would be an asset, but is not required.
- Project 3 qualifications: IIP candidates with interests in computer science are encouraged to apply. Experience in media design and computer/human interaction would be an asset. Experience in object-oriented programming is required (ideally experience in C++ and Python).
- Project 4 qualifications: IIP candidates with interest and experience in business and marketing are encouraged to apply. Experience in the U.S. health care industry would be an asset.