Helmholtz & Israel Exchange Program

Bewerben Sie sich für einen Forschungsaufenthalt in Israel!

Bild: asharkyu/Shutterstock.com

Dieser (virtuelle) Austausch ist Ihre Chance, in diesem Jahr an spannenden Projekten mit israelischen Datenwissenschaftlerinnen und Datenwissenschaftlern an Israels Top-Forschungseinrichtungen zusammenzuarbeiten: 

  • Ben-Gurion University of the Negev
  • Technion - Israel Institute of Technology
  • Tel Aviv University
  • Bar Ilan University
  • University of Haifa

     

Wir freuen uns, bei diesem Austausch mit der Israel Data Science Initiative (IDSI) zusammenzuarbeiten.

   

    

Über das Austauschprogramm

Sie werden mit einem Senior Data Scientist aus Israel an einem Projekt Ihrer Wahl zusammenarbeiten (siehe unten). Aufgrund der Pandemie ist dieses Austauschprogramm „online first“ geplant:

  • Wenn die Reise im Sommer 2021 möglich ist, können Sie die israelischen Partner für sechs Wochen besuchen und mit einem Team vor Ort zusammenarbeiten. Die Reisekosten und die Unterkunft Ihres Besuchs werden von der Helmholtz Information & Data Science Academy übernommen. 
  • Sollte eine Reise im Sommer 2021 nicht möglich sein, können Sie an dem Projekt online von zu Hause aus arbeiten (als Nebenprojekt zu Ihrer Forschung) - mit der Möglichkeit, Ihr Projekt vor Ort abzuschließen, sobald eine Reise sicher möglich ist (bis Dezember 2022).

   

 Warum sollte ich an dem Austausch teilnehmen?

  • Dieses Programm ist eine Gelegenheit, internationale Kollaborationen aufzubauen - mit der Möglichkeit, gemeinsam mit Wissenschaftlerinnen und Wissenschaftlern an Israels Top-Forschungsuniversitäten zu veröffentlichen.

  • Lernen Sie neue Methoden und Skills von erfahrenen Datenwissenschaftlerinnen und Datenwissenschaftlern, die an interessanten Forschungsproblemen arbeiten.

   

Wie ist der Zeitplan?

Bewerbungen öffnen am 15. März 2021 und schließen am 07. Mai 2021.

Informationen zur Programmteilnahme Ende Mai.

Projekte/Austausche können jederzeit danach beginnen. Besuche vor Ort können bis spätestens Dezember 2022 stattfinden.

   

Interessiert?

Nehmen Sie an unserer Q&A Session am 7. April 2021 um 14:00 Uhr (Einwahllink) teil und erfahren Sie mehr über die Projekte und Hosts aus Israel. Die Hosts stellen in kurzen Präsentationen Ihre Projekte vor und beantworten Ihre Fragen.

    

Wie nehme ich teil?

Bitte wählen Sie eines der unten aufgeführten Projekte aus und bewerben Sie sich jetzt bis zum 07. Mai 2021.   

  

Haben Sie Fragen?

Bitte kontaktieren Sie uns: hida@helmholtz.de und werfen Sie einen Blick auf das  FAQ-Dokument. Wir freuen uns, von Ihnen zu hören.

   

Übersicht über die Projekte

Rami Puzis - Ben Gurion University of the Negev

Complex Networks are found in cyber security, social networks, communication networks and the Internet, biological networks, financial networks, text analytics and more. Scientific programmers working the CNA Lab @ BGU develop generic software tools and libraries to analyze the structure of networks derived from the various problem domains. Graduate research students apply these tools to investigate specific problems in their domain of interest.

Link:

https://faramirp.wixsite.com/puzis

What is the data science project's research question?

Which random network topologies result in diffusion dynamics that match real data, given an epidemic propagation model? 

What data will be worked on?

Simulations & public records of COVID-19 infections. The data is open source.

What tasks will this project involve?

Programming in Python/PyTorch, developing DL architecture, analyzing data.

What makes this project interesting to work on?

Unique approach for random network generati and deep dive into optimization in deep learning.

What is the expected outcome?

Contribution to research paper and to software development.

What infrastructure, programs and tools will be used? Can they be used remotely?

Google colab. In case of need our department's GPU cluster will be available through VPN access.

What skills are necessary for this project?

Data analytics / statistics, scientific computation, computer simulations, deep learning, high-performance computing.

Interested candidates should be at PhD level.  Rami Puzis is looking for 2 visiting scientist, working on the project together with the team.

Rami Puzis - Ben Gurion University of the Negev

Complex Networks are found in cyber security, social networks, communication networks and the Internet, biological networks, financial networks, text analytics and more. Scientific programmers working in the CNA Lab @ BGU develop generic software tools and libraries to analyze the structure of networks derived from various problem domains. Graduate research students apply these tools to investigate specific problems in their domains of interest.

Link:

https://faramirp.wixsite.com/puzis

What is the data science project's research question?

Given an image with 1-3 hand strokes, such as the MNIST digits, fit a set of Bezier curves to match the image.   

What data will be worked on?

Generated data and the MNIST dataset. The data is open source.

What tasks will this project involve?

Developing DL/RL architecture, coding in Python/PyTorch.

What makes this project interesting to work on?

Unique deep learning task. Teaching a computer to actually draw.  

What is the expected outcome?

Contribution to research paper and to software development.

What infrastructure, programs and tools will be used? Can they be used remotely?

Python/PyTorch/Google colab - can be used remotely.

What skills are necessary for this project?

Scientific computation, deep learning, some familiarity with OpenCV / computer graphics will help.

Interested candidates should be at PhD level. Rami Puzis is looking for 1 visiting scientist, working on the project individually.

Yaron Orenstein - Ben Gurion University of the Negev

We are very excited to utilize the most advanced machine learning methods to generate more accurate protein-DNA, -RNA and -peptide binding models. The recent advances in neural networks, termed deep learning, have attracted much attention in the field of computational biology. We are applying the methodology successfully to many high-throughput datasets, and plan to take it even further by incorporating several orthogonal sources to improve in vivo binding prediction.

Link:

https://in.bgu.ac.il/en/engn/ece/pages/staff/yaronore_en.aspx

What is the data science project's research question?

The project will involve applications of deep neural networks to high-throughput genomics datasets. It will require improved prediction performance compared to extant tools as well as improved interpretability.

What data will be worked on?

High-throughput genomics datasets in the form of thousands or even millions of DNA/RNA or amino acid sequences and associated labels. The data is open source.

What tasks will this project involve?

Developing a new algorithm to infer predictive models from the data, implementing it in one of the common programming languages, and running the algorithm to measure its performance and compare to existant methods.

What makes this project interesting to work on?

Bioinformatics is seeing a flood of high-throughput data in recent years with many open computational question to answer. The datasets are large enough to infer meaningful models, while each data point is relatively small which makes training and developing a model a fast process. Many datasets are publicly available.

What is the expected outcome?

Contribution to research paper.

What infrastructure, programs and tools will be used? Can they be used remotely?

Python programming, Keras and TensorFlow packages, Unix operating system. Yes, the computing server can be accessed remotely.

What skills are necessary for this project?

Data analytics / statistics, Scientific computation, Computational models, Data mining / Machine learning, Deep learning, High-performance computing.

Interested candidates should be at PhD level. Yaron Orenstein is looking for 1 visiting scientist, working on the project individually.

Hanoch Senderowitz - Bar-Ilan University

Our lab develops, implements and applies new Machine Learning techniques in different areas such as chemistry, biosciences, materials sciences and forensic sciences. We apply problem-dependent workflows consisting of data acquisition, sample characterization, data visualization, descriptors calculations, and model development, validation and application. Tools developed in our groups are made accesible to the scientific community.

Link:

https://research.biu.ac.il/labs/prof-senderowitz-lab/

What is the data science project's research question?

Can machine learning models developed on raw spectral data from elemental analysis provide new capabilities in forensic sciences?

What data will be worked on?

Raw spectral data obtained from elemental analysis. The data is not open source.

What tasks will this project involve?

Developing machine learning models.

What makes this project interesting to work on?

Machine learning tools based on state of the art elemental analysis may provide law enforcement agencies with new capabilities to analyze crime scenes and thus solve a host of forensic related problems. 

What is the expected outcome?

Contribution to research paper and to the development of forenso-informatics.

What infrastructure, programs and tools will be used? Can they be used remotely?

Mainly Python-based tools which could be accessed and used remotely.

What skills are necessary for this project?

Data analytics / statistics, Scientific computation, Data mining / Machine learning, Deep learning, Visualization.

Interested candidates should be at PhD level. Hanoch Senderowitz is looking for 1 visiting scientist, working on the project together with the team.

Eitan Rubin - Ben Gurion University of the Negev

We are working on precision oncology: creating better tools for fitting treatments to tumors. This involves (among other things) stratification of tumors into sub-types, and predicting which sub-types are more responsive to which drugs.

Link:

https://rubinlab.wixsite.com/website/aboutt2

What is the data science project's research question?

Unsupervised stratification of tumors OR supervised learning of tumor response to drugs.

What data will be worked on?

TCGA expression data (60K features, 20K instances) = public datasets /The data is open source.

What tasks will this project involve?

Developing a best-practice data science pipeline for patient stratification predicting drug response.

What makes this project interesting to work on?

On the one hand, it requires best-practice data sciences, on the other hand it has the potential to effect the lives of thousands of patients.

What is the expected outcome?

Contribution to research paper as well as to software development, Clinical Trial and new guidlines.

What infrastructure, programs and tools will be used? Can they be used remotely?

Most of the work can be done on personal computers. If necessary, it can be run on the BGU-HPC cluster.

What skills are necessary for this project?

Data analytics / statistics, Data mining / Machine learning.

Eitan Rubin is willing to train anyone with good computing skills. He is looking for 2 visiting scientist, working on the project together with the team.

Izhar Bar-Gad - Bar-Ilan University 

Our group studies the underlying neuronal mechanism underlying behavioral disorders associated with the basal ganglia, including Tourette syndrome, attention deficit hyperactivity disorder (ADHD) and obsessive compulsive disorder (OCD). We use a combination of tools stemming from systems neurophysiology and computational neuroscience to explore this mechanism. Our studies performed on freely behaving rodents enables the analysis of the relation between complex normal and pathological behavior and the underlying neuronal mechanism. 

Link:

https://www.ibglab.org/

What is the data science project's research question?

The project aims to generate an embedding of the animal movement, given by video streams and kinematic sensors, in a subspace enabling efficient clustering of behaviors.

What data will be worked on?

The data will consist of video and kinematic sensors (accelerometers and gyros) measuring the pose and movement of the rodent.The data is not open source.

What tasks will this project involve?

The project will involve the development of a deep embedding algorithm for addressing multimodal information. 

What makes this project interesting to work on?

The project provides access to an exciting unique dataset of animal behavior and enables addressing key question on the borderline between ethology and neuroscience.

What is the expected outcome?

Contribution to research paper.

What infrastructure, programs and tools will be used? Can they be used remotely?

Standard python environment running on the lab linux servers. 

What skills are necessary for this project?

Deep learning.

Interested candidates should be at PhD level.  Izhar Bar-Gad is looking for one visiting scientist, working on the project together with the team.

Noam Kaplan -Technion - Israel Institute of Technology

The spatial organization of the genome is closely associated with its functional state, e.g. controlling when and where genes are activated. We combine advanced experimental and computational methods to understand how 3D genome organization is specified and how it mediates biological function.

Link:

https://kaplanlab.technion.ac.il/

What is the data science project's research question?

The most basic form of DNA organization is its folding into nucleosome structures, where ~147 basepairs are wrapped around a protein complex. The exact positions of nucleosomes, i.e. which exact DNA sequences are wrapped, are not random and can control the accessibility of factors that read DNA. It is known that specific patterns of nucleosome positioning are associated with the binding of different factors as well as higher order structures, but this is poorly understood. We would like to attempt to use machine learning to predict large scale 3D genome organization (measured experimentally) using only nucleosome positioning patterns (measured experimentally). If successful, this would suggest an unappreciated link between genome organization across scales, and could potentially shed insight on specific nucleosome patterns and their biological meaning.

What data will be worked on?

The data is based on next generation DNA sequencing-based experiments which measure nucleosome organization (using MNase-seq) and 3D genome organization (using Hi-C). Nucleosome organization is a very large vector (n), 3D genome organization is a very large matrix (n^2).

The data is open source.

What tasks will this project involve?

The project will involve using machine learning (most likely deep learning) to find a model that predicts 3D genome organization from nucleosome organization using cross validation etc. Ideally this model should have some interpretable features. It would be great if the candidate would be experienced in applying deep learning in an appropriate setting (we are more experienced in classical machine learning).

What makes this project interesting to work on?

If successful, this would suggest an unappreciated link between genome organization across scales, and could potentially shed insight on specific nucleosome patterns and their biological meaning. These are fundamental systems shared by all complex beings.

What is the expected outcome?

Contribution to research paper and to software development.

What infrastructure, programs and tools will be used? Can they be used remotely?

We mostly use python on a linux HPC.

What skills are necessary for this project?

Data mining / Machine learning, Deep learning.

Interested candidates should be at PhD level. Noam Kaplan is looking for 1 visiting scientist, working on the project individually.

Dr. Yossi Oren - Ben Gurion University of the Negev

Security research is not just fun: it can have a real impact on keeping our society free and safe. The field of implementation security deals with studying the security of actual physical systems, both by attacking them and by proposing ways to defend against attacks. Even the best, most secure algorithm is useless if it’s not implemented carefully, and our job is to make sure that happens.

One main purpose of the Implementation Security Lab is to carry out side-channel attacks -– cyber attacks that allow the extraction of secret information from various devices by exploiting their precise physical behaviors (such as power consumption, electromagnetic emanations, heat or vibration).

Link:

https://orenlab.sise.bgu.ac.il

What is the data science project's research question?

Can deep learning be used to create more efficient and accurate classifiers for micro-architectural fingerprinting.

What data will be worked on?

Micro-architectural fingerprints generated in our lab and through cooperation with international partners. The data is open source.

What tasks will this project involve?

Analyzing the data,  evaluating the existing ML pipeline, suggesting improvements to the collection, processing and classification components, writing a journal article.

What makes this project interesting to work on?

State of the art research aimed at a A* venue, joining a very cool existing international team.

What is the expected outcome?

Contribution to research paper.

What infrastructure, programs and tools will be used? Can they be used remotely?

Matlab or another software, can be used remotely.

What skills are necessary for this project?

Data analytics / statistics, Data mining / Machine learning.

Interested candidates should be at PhD level. Yossi Oren is looking for 1 visiting scientist, working on the project together with the team.

Hadas Okon-Singer  - University of Haifa

We study the neurocognitive mechanisms underlying cognition-emotion interactions. In different projects, we examine cognitive biases that characterize psychiatric disorders, including biased attention, interpretation, expectancy and perception, and the causal links between these biases.

The project here is a continuation of a project done at my lab. In this project, we developed a battery for assessing cognitive biases. Machine learning based analysis is planned in order to detect patterns that characterize anxiety and depression, and better differentiate these two psychiatric disorders.

Link:

https://ceilaboratory.wixsite.com/labsite

What is the data science project's research question?

Whether anxiety and depression can be better diagnosed based on implicit performance measures, as opposed to the current self-report based diagnosis.

What data will be worked on?

Behavioral data collected from subclinical and clinical samples. The data is open source.

What tasks will this project involve?

Machine-learning analysis of the data, algorithm development.

What makes this project interesting to work on?

First, the use of machine-learning analysis in the context of psychiatric diagnosis is innovative, and it is of high importance theoretically and clinically. Second, from a data-science perspective, we have already collected a rich and unique data and the options to analyze it in different methods offers several opportunities to develop new influential analysis tools and algorithms.

What is the expected outcome?

Contribution to research paper.

What infrastructure, programs and tools will be used? Can they be used remotely?

Matlab or another software, can be used remotely.

What skills are necessary for this project?

Data analytics / statistics, Data mining / Machine learning.

Interested candidates should be at PhD level. Hadas Okon-Singer is looking for 1 visiting scientist, working on the project together with the team.

Sagi Dalyot - Technion -  Israel Institute of Technology

People with mobility disabilities face numerous challenges in their daily life and activities, with evident difficulties that include their orientation, navigation, and wayfinding in urban spaces. The research will involve the development of AI-based models that learn existing optimal routes frequently traveled by people with mobility disabilities (e.g., visually impaired pedestrians, people in wheelchairs) to calculate optimal parameters, weights and criteria for developing route calculation engine(s) that generates customized safe and accessible routes.

Link:

https://ecsl.net.technion.ac.il/

What is the data science project's research question?

What are the main urban-related physical and temporal influences - manifested in geographic data - on the mobility preferences of people with mobility?

What data will be worked on?

Geographic information system (GIS) related, e.g., layers, thematic and road networks, mainly from OpenStreetMap (SOM). The data is open source.

What tasks will this project involve?

Assimilation of GIS data, road network analysis, ML/DL models.

What makes this project interesting to work on?

This project has a strong social impact on certain communities in our society, which face daily difficulties and social isolation that negatively affects their wellbeing. The outcome can be implemented in practical location-based services, encouraging and enabling them to go out more, and thus helping them to be an equal part of our society.

What is the expected outcome?

Contribution to research paper and to software development.

What infrastructure, programs and tools will be used? Can they be used remotely?

GIS-software (e.g., QGIS), Python (e.g., PyCharm). All processes and developments can be done remotely.

What skills are necessary for this project?

Data analytics / statistics, Data mining / Machine learning, Deep learning, Geographic Information Systems.

Interested candidates should be at PhD level. Sagi Dalyot is looking for 1 visiting scientist, working on the project together with the team.

Raja Giryes -Tel Aviv University 

My group focus on different aspects of deep learning. Specifically, we study few shot learning, image processing, computational imaging and theory of deep learning. 

Link:

web.eng.tau.ac.il/~raja

What is the data science project's research question?

Can we improve image reconstruction for real data using deep neural networks? 

What data will be worked on?

Real low quality images. The data is open source.

What tasks will this project involve?

Adapting a neural network to real images.

What makes this project interesting to work on?

Most networks that are trained today are fitted to artificial data. We want to make the networks work on real data.

What is the expected outcome?

Contribution to research paper.

What infrastructure, programs and tools will be used? Can they be used remotely?

GPU servers. Everything can be accessed remotely.

What skills are necessary for this project?

Deep learning.

Interested candidates should be at PhD level. Raja Giryes is looking for 2 visiting scientist, working on the project together with the team.

Yoav Ram - Tel Aviv University 

We study evolution, ecology, cultural evolution, and epidemiology, using mathematical, computational, statistical, and machine-learning models and collaborations with empirical biologists.

Link:

http://www.yoavram.com

What is the data science project's research question?

Can the global variation in culinary recipes be understood in terms of cultural, geographical, and climatic variation?

What data will be worked on?

Recipes from allrecipes.com, epicurious.com, and menupan.com. The data is open source.

What tasks will this project involve?

Data preparation and exploration, analysis using methods such as unsupervised manifold learning (PCA, T-SNE, UMAP), Procrustes analysis, Mantel test.

What makes this project interesting to work on?

Food is universal, but recipes are diverse and dynamic. Exploring the correlations between recipes, culture, geography, and climate could help us understand the dynamics of cultural evolution.

What is the expected outcome?

Contribution to research paper.

What infrastructure, programs and tools will be used? Can they be used remotely?

Access to computing cluster, software for statistics and machine learning (e.g. Python or R).

What skills are necessary for this project?

Data analytics / statistics, Visualization.

Interested candidates should be at PhD level. Yoav Ram is looking for 1 visiting scientist, working on the project individually.

Yoav Ram - Tel Aviv University 

We study evolution, ecology, cultural evolution, and epidemiology, using mathematical, computational, statistical, and machine-learning models and collaborations with empirical biologists. 

Link:

http://www.yoavram.com

What is the data science project's research question?

Can results of microbial competitions be predicted from mono-culture growth curves?

What data will be worked on?

Growth curves and competition assay results from previous publications. Some data is open, some not.

What tasks will this project involve?

One of (1) re-implementing an existing software tool that uses standard curve fitting to use Bayesian model fitting, or (2) extending existing software tool that uses a standard growth model to use more complex growth models.

What makes this project interesting to work on?

The basic approach has already been published (http://doi.org/10.1073/pnas.1902217116), but more complex inference or models can provide further details and more applications to a wider array of organisms and questions.

What is the expected outcome?

Contribution to research paper and to software development.

What infrastructure, programs and tools will be used? Can they be used remotely?

Empirical datasets, computing cluster, Python programming language.

What skills are necessary for this project?

Data analytics / statistics, Scientific computation, Computer simulations.

Interested candidates should be at PhD level. Yoav Ram is looking for 1 visiting scientist, working on the project individually.

Ron Shamir - Tel Aviv University 

We develop algorithms and tools for analysis of genomic, medical and systems biology data.

Link:

acgt.cs.tau.ac.il

What is the data science project's research question?

Bring active gene module discovery tools to the biologist workbench.

What data will be worked on?

Gene expression, genome-wide association studies,  biological networks. The data is open source.

What tasks will this project involve?

Develop a server based on existing batch code. Improve the algorithm if time allows.

What makes this project interesting to work on?

Combination of exciting data types; Bring active gene module discovery tools to the biologist's workbench.

What is the expected outcome?

Contribution to software development.

What infrastructure, programs and tools will be used? Can they be used remotely?

Standard and our lab-developed tools. Yes, can be used remotely.

What skills are necessary for this project?

Data analytics / statistics, Computational models, Visualization.

Interested candidates should have proficiency in programming.  Ron Shamir is looking for 1 visiting scientist, working on the project together with the team and being supervised by someone else.

Tirza Routtenberg and Jonathan Rosenblatt  - Ben Gurion University of the Negev

Our labs cover a wide range of domains in statistics, signal-processing, and machine-learning. We do theory, application, and implementation of solutions in signal processing, brain-imaging, environmental monitoring, power systems, and more.  

Link:

https://www.researchgate.net/lab/Tirza-Routtenberg-Lab

https://www.john-ros.com/ 

What is the data science project's research question?

How to scale numerical simulations for designing sensor arrays?

What data will be worked on?

Our data includes seismic and infrasound measurements from in international network of sensors. The data is open source.

What tasks will this project involve?

Writing a simulator in python:
1. Implementing the estimator.
2. Implementing the data generation process.
3. Searching for an optimal array geometry.
4. Scaling 1-3 to deal with hundreds of sensors, and complicated geometries. 

What makes this project interesting to work on?

The project as at the intersection of statistical estimation, signal processing, and numerical analysis.  The methods and "tricks" used to scale the search for optimal geometries are a valuable tool-set for scaling up any learning problem: be it simple parameter estimation or internet-scale deep learning.

What is the expected outcome?

Contribution to research paper and to software development.

What infrastructure, programs and tools will be used? Can they be used remotely?

Yes. VPN access to BGU infrastructure will be provided. 

What skills are necessary for this project?

Scientific computation, Computer simulations, High-performance computing.

Interested candidates should be at PhD level. Tirza Routtenberg and Jonathan Rosenblatt are  looking for 1 visiting scientist, working on the project individually.

Guy Avni - University of Haifa

Traditionally formal methods aim at formally verifying the correctness of reactive systems, which can be thought of as controllers for plants. We study “reactive synthesis” in which the goal is to construct a correct-by-design controller. We study the theoretical foundations of this problem; namely, game theory and in particular graph games, which are needed to properly model the interaction between a controller and the plant. We also study applications of synthesis in combination with trained controllers.

Link:

https://sites.google.com/view/gavni

What is the data science project's research question?

Formal methods and machine learning have complimentary advantages and disadvantages. While trained controllers exhibit unprecedented plant performance and scalability, they supply no worst-case guarantees, which is an obstacle in deploying these systems in practice, especially in safety-critical domains. The goal of this research is to study ways to combine ideas from reactive synthesis and (deep) reinforcement learning to obtain the best of both worlds: a scalable technique that achieves high-quality controllers with worst-case guarantees. 

What data will be worked on?

We train our controllers using deep reinforcement learning. The data is open source.

What tasks will this project involve?

Training controllers, synthesizing components on top of a trained controller, and conducting experimenting. We expect the research project to be iterative: the theory will drive the initial experiments but their results will probably lead to adjustments in the theory, which will call for experiments, and so forth.  

What makes this project interesting to work on?

Deploying a trained controller "in the wild" is a real and important challenge; e.g., see accidents in Tesla's autonomous vehicles. Addressing this challenge using a combination with formal methods is promising. In addition, the project is multi-disciplinary and involves both theory and practice. 

What is the expected outcome?

Contribution to research paper.

What infrastructure, programs and tools will be used? Can they be used remotely?

Coding and experiments will be done on personal computers and can be done remotely. 

What skills are necessary for this project?

Scientific computation, Computational models, Programming skills in Python.

Interested candidates should be at PhD level. Guy Avni is looking for one visiting scientist, working on the project together with the team.

Arnon Hershkovitz - Tel Aviv University 

My group's research lies in the intersection of learning, teaching, and technology. Mostly, we're interested in the skills requested for, and shaped by, today's settings of learning and teaching, which are part of a cyberlearning ecosystem; these are studied using Learning Analytics and other methodologies.

Link:

https://sites.google.com/view/arnon-hershkovitz/home

What is the data science project's research question?

What is the role of creativity in the acquisition of computational thinking?

What data will be worked on?

Log files drawn from an online learning environment for computational thinking; the files document activity of ~26,000 K-12 students over a few months, with an overall of ~300K records; log files drawn from another learning environment for computational thinking will be considered. The data is not open source.

What tasks will this project involve?

1. Modeling creativity, based on learners' records from the log files. The conceptual model of creativity is based on a well-established framework. The main component of the model would categorize learners' programming codes based on the CS constructs they use, and based on similarity to codes. Methods for identification and similarity-checking will be discussed as part of the project.
2. Developing measures of computational creativity, based on learners' progress in the learning environment.
3. Once a model is built and measures are operationalized, we would study association between creativity and the acquisition of computational thinking.

What makes this project interesting to work on?

Contribution to the field of education is tremendously important. Furthermore, studying creativity in a log-based manner is innovative. Finally, we are very nice people to work with ;-) .

What is the expected outcome?

Contribution to research paper and to software development.

What infrastructure, programs and tools will be used? Can they be used remotely?

Any tool that will support data crunching and analysis is welcomed!

What skills are necessary for this project?

Data analytics / statistics, Scientific computation, Computational models, Data mining / Machine learning.

Interested candidates should be at PhD level. Arnon Hershkovitz is looking for 1 visiting scientist, working on the project individually.

Tirza Routtenberg and David Lukatsky - Ben Gurian University of the Negev

We will develop novel computational tools to investigate DNA sequence repeats in genomes. This analysis will be implemented to understand fundamental design principles of gene expression. The analysis is based on fundamental tools in digital signal processing (DSP).

Link:

https://www.researchgate.net/lab/Tirza-Routtenberg-Lab

http://www.bgu.ac.il/~lukatsky

What is the data science project's research question?

How can we implement an analysis of DNA sequence repeats using the Fast Fourier Transform?

What data will be worked on?

Next generation high-throughput sequencing data. The data is open source.

What tasks will this project involve?

Development of computational tools, application of the method to analyze genome data.

What makes this project interesting to work on?

This is a multidisciplinary project involving both computer science, signal processing, and genomics.

What is the expected outcome?

Contribution to research paper and to software development.

What infrastructure, programs and tools will be used? Can they be used remotely?

Public genomic data. Matlab programming. Can be accessed remotely.

What skills are necessary for this project?

Data analytics / statistics, Scientific computation, Computational models, Computer simulations.

Interested candidates should be at PhD level. Tirza Routtenberg and David Lukatsky are looking for 1 visiting scientist, working on the project together with the team.

     

Israel Data Science Initiative

IDSI vereint und koordiniert die Aktivitäten der Forschungszentren für Datenwissenschaft an allen israelischen Universitäten. Es dient als Repräsentant für alle Belange der Datenwissenschaft sowohl für die Industrie als auch für öffentliche Einrichtungen und fördert internationale Kooperationen für seine Mitglieder.

Die Hauptaktivitäten von IDSI beziehen sich auf die Bereiche Forschung, Bildung und Outreach für den staatlichen und industriellen Sektor. Für die Forschung fungiert IDSI als Brücke zwischen den lokalen DS-Forschungszentren und Forschungsorganisationen auf der ganzen Welt, die sich auf die Entwicklung von Data-Science-Methodik und -Praxis konzentrieren. Für die Bildung wird das IDSI die Entwicklung von akademischen DS-Kursen erleichtern, mit besonderem Schwerpunkt auf der Zusammenarbeit zwischen den Universitäten, sowie die Förderung von Online-Kursen für eine breitere Nutzung. Für den Bereich Outreach wird das IDSI mit Regierungsbehörden wie dem Central Bureau of Statistics zusammenarbeiten, um den Zugang zu Umfrage- und Verwaltungsdaten zu erweitern, und es wird mit der Industrie zusammenarbeiten, um sowohl eine Ressource für DS-Expertise bereitzustellen als auch Schulungsprogramme zu ermöglichen.

    

Fragen? Rückmeldung? Nehmen Sie Kontakt auf mit: 

    

Danielle Metzler

  • Referentin Talent & Technology Scout Helmholtz Information & Data Science Academy (HIDA), Bereich Strategische Initiativen
  • Helmholtz-Gemeinschaft
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