Dear all,

At TU Delft, we have a vacant position in our statistics section. For more details, please view the vacancy text:

https://www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details/?jobId=597&jobTitle=Assistant%20Professor%20or%20Associate%20Professor%20Statistics

The application deadline is September 30. Feel free to forward the announcement to potential candidates!

With best regards, Geurt

Prof. dr. ir. Geurt Jongbloed

*D*elft *I*nstitute of *A*pplied *M*athematics

Faculty *E*lectrical *E*ngineering, *M*athematics and *C*omputer *S*cience

*T**U **Delft*

W http://diamweb.ewi.tudelft.nl/~geurt/

Assistant: Cecilia van der Hoeven

T+31 (0)15 27 81939 Esta dirección de correo electrónico está siendo protegida contra los robots de spam. Necesita tener JavaScript habilitado para poder verlo.

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
Email: Esta dirección de correo electrónico está siendo protegida contra los robots de spam. Necesita tener JavaScript habilitado para poder verlo.

The Basque Center for Applied Mathematics (BCAM, Bilbao, Spain) has opened two postdoctoral positions in Applied Statistics (more info at the end of the email). I would appreciate it if you help us disseminating the position. If you know someone that could be interested, please forward her/him the information. The deadline is July 13th, 2020.

---- Job offers ----
1) Postdoctoral Fellowship in Applied Statistics at the BCAM (Basque Center for Applied Mathematics, Bilbao)
Topics: Fair Learning in Health. Development of mathematical models aimed at detecting and ensuring non-discriminatory and fair decisions based on artificial intelligence algorithms. Special focus will be placed on health applications.

Principal Investigator in charge: Maria Xose Rodriguez Alvarez
No Positions offered: #1
Contract and offer: 2 years
Deadline: July 13th 2020, 14:00 CET (UTC+1)
More info: http://www.bcamath.org/documentos_public/archivos/ofertas/Postdoc_AS.pdf
How to apply: Applications must be submitted on-line at http://www.bcamath.org/en/research/job

2) Postdoctoral Fellowship in Applied Statistics at the BCAM (Basque Center for Applied Mathematics, Bilbao)
Topics: Development of mathematical/statistical methods and computational tools for modelling the transmission dynamics of SARS-Cov-2 with a special focus on the prediction of health care resources. Our proposal rests on the combination of mechanistic models and Bayesian inference for uncertainty quantification and the development of efficient Markov Chain Monte Carlo (MCMC) samplers and numerical algorithms for the real-time use of the results. The selected candidate will work with members of the research lines of "Applied Statistics" and "Modelling and Simulation in Life and Material Sciences" of the BCAM.

Principal Investigator in charge: Maria Xose Rodriguez Alvarez and Elena Akhmatskaya
No Positions offered: #1
Contract and offer: 1 years
Deadline: July 13th 2020, 14:00 CET (UTC+1)
More info: http://www.bcamath.org/documentos_public/archivos/ofertas/BCAM_postdoc_COVID_AS.pdf
How to apply: Applications must be submitted on-line at http://www.bcamath.org/en/research/job

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, Esta dirección de correo electrónico está siendo protegida contra los robots de spam. Necesita tener JavaScript habilitado para poder verlo., or see his website https://warwick.ac.uk/fac/cross_fac/zeeman_institute/staffv2/burroughs/.