The UC3M-Santander Big Data Institute (IBiDat) (www.ibidat.es) is a joint initiative by Universidad Carlos III de Madrid and Banco Santander. It was founded in 2015 and it has rapidly become an institution of reference in the area of Big Data Analytics in Spain. IBiDat’s goal is to apply cutting-edge research to solve industry problems, participate in research and innovation projects funded by different national, European and international agencies and develop specific industry-based training and teaching activities in the area of Big Data Analytics. The Institute counts with a team of 7 full-time outstanding researchers as well as more than 40 fellow affiliated researchers from multiple disciplines: statistics, economics, finance, computer science, engineering, etc.
IBiDat is located in Madrid, one of the most livable and enjoyable cities in Europe that offers an exceptional offer of recreational activities.
As a high quality research institute, the PostDocs in IBiDat should be capable of performing those tasks expected from an early career faculty in academia adapted to the institute’s focus on R&D applied to industry challenges. This offers our PostDocs a twofold career development in both academia and industry towards his/her next professional step.

Position Overview

The main tasks performed by IBiDat PostDocs include:
- Lead and participate in R&D projects with private companies.
- Lead and participate in proposal preparation for competitive public
and private funding programs such as: EU programs (H2020 and Horizon Europe), National and Regional Research Programs and Private Companies Research Programs.
- Preparation and participation in Big Data and Machine Learning courses and masters.
- Conduct high quality research that leads to publications in top venues (journals and conferences).

Conditions
- Salary: 32,000 €/ year.
o Extra economic compensation might be possible through the participation in projects and/or teaching activities of the Institute.

- Duration: 2 years (1+1). The continuation for the second year (upon available funding) will be confirmed through a performance assessment of the first year.
o Extension further than 2 years could be possible, subject to funding availability and performance criteria.

- Starting Date: September 2020.

Requirements
- A PhD degree in Statistics, Mathematics, Computer Science, Engineering, Finance or related fields on the starting date.

- Experience in R&D projects with companies or from public funding programs.

- Good publication record in top journals and/or conferences in the discipline of the candidate.

- Technical Skills:
o Strong analytical and modelling skills
o Knowledge of Data Analysis Programming Languages: R, Python and/or Spark.
o Knowledge DataBases: mysql, neo4j, etc.
o Knowledge of Machine Learning Algorithms.

- Capacity to work both individually and as part of a team.
- Good communication skills.

Application Instructions
- Interested candidates should send by email:
o A statement of interest including the objectives to be achieved in the position.
o A curriculum vitae (with picture included).

- The candidate should also ask two referees to send letters of reference.
- DEADLINE for applications: July 10, 2020.
- All the candidate’s information and reference letters must be sent to:

Cristina Fdez-Oruña Fdez-Escalante
Office 18.2.D26 Phone: +34 91 624 85 14
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In the context of Frank Hutter's ERC grant on automated deep learning and several other grants for basic research, there are multiple positions open for outstanding postdocs, as well as outstanding research engineers, in AutoML in Freiburg, Germany. Starting dates are flexible, but the application deadline is March 15th.

The funding for these positions is for *basic research* on AutoML -- pure methods development without the need for any particular application. Our focus is on automated deep learning, neural architecture search, efficient hyperparameter optimization, learning to learn, and AutoML in general, and we have a track record of developing widely-used open-source tools, such as Auto-sklearn (https://github.com/automl/auto-sklearn).

The salary scale for full-time positions is TV-L E13 to TV-L E14, with a monthly gross salary between 4000 EUR and 4600 EUR, depending on experience and previous position. Please see the full job posting at https://www.automl.org/jobs-at-ml-freiburg/ for details.
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Full time, fixed term PDRA/research fellow for 36 months (possible extension by additional 12 months).
Closing date 28th June 2020.
Flexible starting date, but ideally Oct 2020-Jan 2021.
Salary: £30,942 - £40,322 per annum.
Apply through website Research Fellow (Sequential Design and Statistical Analysis of Human Egg Development (102007-0520)
Subject areas: Experimental design, multi-variate analysis, clustering/stratification/categorisation, and/or Bayesian experimental design, MCMC. Potentially relevant are rare events analysis, Gaussian processes and mixture modelling.

Project: Applications are invited for a 3yr PDRA position to work on the experimental design and statistical data analysis of chromosome organisation in human egg development. The project will involve two main tasks - firstly, determining optimal (sequential) egg assignment amongst a range of experiments using experimental design techniques and, secondly, analysis of complex heterogeneous data sets using multi-variate analysis and clustering methods to determine the power of these experiments for answering key hypotheses and identifying the causal factors/correlates of misorganisation events (eg aberrant organisation patterns). Egg assignment will be particularly important since the numbers of eggs is limited and misorganisation is a rare events (1 in 10 or less). Bayesian analysis methods, such as Bayesian experimental design and Bayesian inference using (hierarchical) Markov chain Monte Carlo, may potentially be required given the data complexity and heterogeneity.

Background: Chromosome organisation during egg development is a complex mechanical process that in humans is poorly understood. You will join a large interdisciplinary team joint between Warwick and Edinburgh using donated human eggs (~50/mth) to understand how eggs develop and acquire a single complete copy of the genome. You will undertake the analysis of the data generated on the project by utilising a range of computational and statistical methodologies. This includes sequential experimental design techniques and multi-variate analysis, and may include use of optimisation methods, clustering/stratification methods, rare events analysis, Gaussian processes and mixture modelling. The project can also involve image analysis for interested applicants. The overall aim of the project is to deliver the first comprehensive analysis of chromosome separation during egg development and during the early embryonic cell divisions in humans. This project thus has direct relevance to understanding human infertility.

Desirable skills: The ideal candidate will have a PhD in a relevant subject such as statistics, mathematics, physics, operations research, computer science or data science, and have a strong statistics background. Candidates with either Bayesian or traditional statistical backgrounds are encouraged to apply. Having experience with experimental design, analysis of large complex multi-variate data sets or developing algorithms for (statistical) analysis of complex (heterogeneous) data sets will be an advantage. Candidates should be able to programme in a high level language such as R, MatLab, C++ or similar. A willingness for communicating with biologists is encouraged. A background in biology is NOT required.

Application is via the HR website
Research Fellow (Sequential Design and Statistical Analysis of Human Egg Development (102007-0520) and should include 1) a letter of application outlining previous research experience/significant results and why you are interested in the post, 2) a CV, 3) a list of publications, and 4) links to a small selection of reprints/preprints/publications from your PhD/latest research post as appropriate.

Scientific queries about the project can be made to Prof Burroughs, Este enderezo de correo está a ser protexido dos robots de correo lixo. Precisa activar o JavaScript para velo., or see his website https://warwick.ac.uk/fac/cross_fac/zeeman_institute/staffv2/burroughs/.

Apologies for any double posting. We are looking for applications for a PhD scholarships in a multidisciplinary topic (OR+Finance).

Kind regards,

Belen

Baillie Gifford PhD in Financial Technology Scholarship (applications of Artificial Intelligence and Robust Optimization)

the University of Edinburgh Business School is now accepting applications for a funded 4-year Ph.D. in Financial Technology, specifically around the theme of environmental risks in supply chain networks.

The selected student will collaborate on a project that will study how environmental risks affect supply chain networks and how firms can best adapt their supply chain to protect it against those risks. Specifically, it will combine Artificial Intelligence and Robust Optimisation techniques to study the effects of environmental risks on the supply chain networks and suggest alterations that can make supply chains less vulnerable to environmental shocks and climate change.

Application: Please follow the link below for details on the online application and the PhD curriculum. Applications must be completed by Friday 5 April 2020 to be reviewed for admission.

https://www.business-school.ed.ac.uk/scholarships/baillie-gifford-fintech

The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336.