+Courses and events
Topics for MSc/PhD theses
Welcome to contact us to discuss research/study positions.
We supervise study assignments (BSc/MSc/PhD) on applied statistics / computational science / machine learning / AI theory, methods, and their application to study complex natural and social systems. Active research projects cover scientific data analysis, statistical and probabilistic programming workflows, data visualization, microbial metagenomics, ecological and evolutionary models, multi-omic data integration, spatio-temporal models, computational history, and open government data analysis.
Courses in 2023
July 10-14, 2023, Nijmegen, The Netherlands
- Brain, Bacteria and Behaviour: Understanding the Gut-Brain Axis including microbiome data science with R/Bioconductor
Apr 12-14 2023, Wageningen, The Netherlands
March 21-24, 2023, Pune, India
- Microbiome research: analysis and applications including microbiome data science with R/Bioconductor
March 2023, Turku, Finland (weekly meetings)
Courses in 2022
Contact us if you are interested. The admission varies by course but most courses are open to application.
March-May 2022 - University of Turku, Finland
- Machine Learning and Algorithmics Seminar (TKO_3121 5 op). Drs. Leo Lahti & Matti Ruuskanen
May 24, 2022 - University of Tirana, Albania
June 20-23, 2022 - University of Oulu, Finland
July 11-15, 2022 - Radboud University Nijmegen, The Netherlands
August 2022 - Savitribai Phule Pune University, India
- Microbiome Research Symposium
October 2022 - Barcelona
- ML4microbiome training school
Oct-Dec 2022 - University of Turku
Oct-Dec 2022 - University of Turku, Finland
- Machine Learning and Algorithmics Seminar (TKO_3121 5 op). Drs. Leo Lahti & Matti Ruuskanen
Nov 28 - Dec 1, 2022 - CSC, Finland (virtual course)
Past courses and events: links to material
Open science
- Conference on Philosophy and History of Open Science (#PHOS16) - digital collection - 2016 University of Helsinki, Finland
Computational science and machine learning
Machine Learning and Algorithmics Seminar (TKO_3121 5 op) University of Turku, Finland. With Dr. Matti Ruuskanen 3-5/2021
Probabilistic data analysis research seminar - University of Turku - 2020
Machine Learning and Algorithmics Seminar (TKO_3121 5 op). University of Turku - 3-4/2020
Research seminar on probabilistic machine learning - University of Turku, Finland based on Machine learning - a probabilistic perspective (K. Muprhy). PDF - 2018-2019
Introduction to probabilistic programming - Lecture slides ODP; PDF - 2018 VIB/KU Leuven, Belgium
Microbiome data science
Multi-omics Machine Learning workshop. Jan 13-14, 2022 (virtual - H2020/FindingPheno)
Workshop on modeling microbial community time series. November 2021 (virtual)
ML4Microbiome Symposium on Grand Challenges of Data-Intensive Science in microbiome & metagenome data analysis and training. October 2021 (virtual lecture)
Baltic Summer School on Digital Methods in humanities and social sciences, August 2021 (virtual)
ML4Microbiome Training School, September 2021 (virtual)
Brain, Bacteria and Behaviour: Understanding the Gut-Brain Axis online summer school, The Netherlands, July 2021 (virtual)
NORBIS Summer School 2021; National research school in bioinformatics, biostatistics and systems biology, Norway, Aug 2021 (online)
Microbiome Data Analysis Workshop - Hasselt University, Limburg, Belgium, Apr 2021 (online)
Tools and techniques for skin microbiome research - Savitribai Phule Pune University, Pune, India, Jan 2021
Modern statistics for microbiome bioinformatics - Pune, India, Dec 2019
Intestinal microbiome of humans and animals. VLAG Graduate School course - Wageningen University and Research Center, The Netherlands, Oct 2019
Contemporary themes in microbiome data science. - Singapore Centre for Environmental and Life Science Engineering Sep, 2019
Advanced statistical techniques in microbiome bioinformatics - Sep 2019 Nijmegen
International summer school on microbial community modeling - Sep 2019 KU Leuven, Belgium
International spring school on open and reproducible microbiome data analysis - 2018 Wageningen, The Netherlands
International summer school on microbial network analysis - 2017 KU Leuven, Belgium
Computational humanities
- Baltic Summer School on Digital Methods in humanities and social sciences. Aug, 2021 (online)
Copyright (c) 2020-2021, Leo Lahti; some rights reserved.
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Resources
Tutorials and Data
Microbiome data science
Open government data analytics
Data visualization
Teaching software & online resources
A framework for creating and assessing exercises for R courses (presented in UseR2017!; Markus Kainu)
Open access to educational resources National policy and executive plan by the higher education and research community for 2021-2025 (2020) DOI:10.23847/isbn.9789525995251
Versus online journal for science popularization.
Video lectures and interviews
Integrating open science in the humanities: the case of computational history Springer-Nature blog post and links to the streamed presentations 11/2019
Microcosm within us: gut microbiome Science Cafe, Turku, Finland 3/2018
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Online resources
Blog on open data analytics (rOpenGov)
Versus online journal for science popularization.
Selected video lectures and interviews
Integrating open science in the humanities: the case of computational history Springer-Nature blog post and links to the streamed presentations 11/2019
Microcosm within us: gut microbiome Science Cafe, Turku, Finland 3/2018
Open science interview University of Helsinki, Finland 2/2014
Apps4Finland interview Helsinki, 9/2012
Dependency Modeling Toolkit, ICML/MLSS Workshop. Haifa, Israel 6/2010
Copyright (c) 2020-2021, Leo Lahti; some rights reserved.
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Make your own Jekyll website for your academic research group
This website is powered by Jekyll and uses some Bootstrap and Bootswatch. The page borrows open source code from Allan Lab. The site is simple yet adaptable.
All pages are written in markdown for easy editing, and Jekyll uses Liquid for the data-driven pages. The publication list is automatically generated from bibtex, and requires the jekyll-scholar plugin. The news items, and group members are stored as .yml data sheets (plain text) in the _data folder, so that one can update the website easily. The pages are in the _pages folder. Updating and maintaining is easy using Github (not worldpress-easy, but there are other advantages (see e.g. this, or this). Jekyll takes all the markdown and data files, and creates beautiful html files in the _site folder.
Create and open a github account, go to our repository, and click ‘fork’. This is now your copy of the website, and you can change and adapt it. Then change the name of the repository to “your_username” and the name of the branch to “gh-pages”. Your website is now automatically published under your_username.github.io/your_username/. Except that it probably still looks like our website.
To modify the webpage, you can either do everything on on github.com (go to a file, click “edit”, then “commit”, “push”), or install Jekyll on your computer and play with your local copy that you sync with the branch on github.com. The former is much easier in the beginning, but a bit less convenient once you start rewriting everythint. To get it to work on your computer (and to learn a bit more about Jekyll), here and here are tutorials on how to use it and how set it up locally. Also, consider using the Github desktop app.
Now let’s make this your website.
First, go to the news.ylm, publist.ylm, and team.ylm files in the _data folder and insert your own data into the data fields. Watch out: Jekyll is quite strict about extra or missing spaces etc. Adhere to the format. In the beginning, test each change: commit, push, and check the published website.
For publications, you can add a “1” in the highlight field, then it will be featured prominently. You can add important news items (red, “news1”), and less important news items (blue, “news2”).
For the news items, just keep adding them. The first 10 will be displayed on the ‘home’ page.
For the team.ylm file
Next, change the content of all files in the _pages folder. To change the title in the homepage, go to homelay.html in the _layout folder.
Lastly, change the footer and perhaps header appropriately (in _include).
You might also want to change the style or theme. I imported style files (in sass) from Bootstrap/Bootwatch, you can replace them with your own (in the _sass directory). For small changes, just work on the override stuff in the main.sass file in the CSS folder. Or change some variables in the _variables.sass file, like the background color etc.
As said, Jekyll takes all the markdown and data files, and creates beautiful html files in the _site folder.In the end, either upload these files to your server, or buy yourself a domain and check the instructions on github on how to host it there.
Code released under the MIT License.
Copyright (c) 2020-2021, Leo Lahti; some rights reserved.
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I embed a current version of my CV below. You can also download the PDF here.
{% include embedpdf.html code=“30ah9tgxevj1vl9/svm-cv.pdf” width=100 height=800 %}
Copyright (c) 2020-2021, Leo Lahti; some rights reserved.
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Copyright (c) 2020-2021, Leo Lahti; some rights reserved.
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Links to academic services online: Leo Lahti
Researcher profiles, networks, publication databases and impact altmetrics
Copyright (c) 2020-2021, Leo Lahti; some rights reserved.
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How to publish and archive research software or source code
Choose open license The code is not really “open” without an open license. Common ones include MIT, FreeBSD and GPL3. The MIT license is often recommended due to its simplicity. See Quick guide to software licensing for a scientist programmer. See also the brief memo on open licensing of scientific material.
Add version number
Document the experiments. At the minimum, list where the data is located (preferably link directly in the code) and which scripts should be run to replicate the experiments. Sometimes people use electronic notebooks (Rmd / Jupyter) to share analyses. This can combine the code with automatically generated figures etc and directly show the outputs of the code. Add a README.
Long-term preservation Github is not guaranteed to continue and it is maintained by a private party. It is recommended to make a git “release” and store that in Zenodo with a DOI. Then the DOI provides permanent access to the exact code that was used in the publication, and that zip file will remain available in the academic Zenodo service. If you want you can also create a DOI for the repository. Good to notice that the repository and exact version at a given time may be different things. You can check this and this2 for details.
Tips on data science project git repo organization
- PLoS Comput Biol. 2016 Jul; 12(7): Ten Simple Rules for Taking Advantage of Git and GitHub. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4945047/
- Human in a Machine World. May 25, 2016: Folder Structure for Data Analysis. https://medium.com/human-in-a-machine-world/folder-structure-for-data-analysis-62a84949a6ce
- Cookiecutter Data Science - A logical, reasonably standardized, but flexible project structure for doing and sharing data science work. https://drivendata.github.io/cookiecutter-data-science/
- Thinking on Data. December 9, 2018: Best practices organizing data science projects. https://www.thinkingondata.com/how-to-organize-data-science-projects/
Copyright (c) 2020-2021, Leo Lahti; some rights reserved.
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Seminar on machine learning and data science
We are running a weekly research seminar and journal club on machine learning and data science in University of Turku, Finland. These are open and informal events. The exact location and topics may vary, so contact us if you’re interested!
Research seminar / Reading circle
Thursdays 10-11:30am (2018-2019). We cover material from the following books, a chapter per week.
Machine learning - a probabilistic perspective (K. Muprhy). Free PDF is available.
The elements of statistical learning. Free PDF is available.
Journal club
Tuesdays 9-9:30am (2018-2019). Various papers on statistical machine learning, data science, and applications.
Mission
Ten simple rules for journal clubs gives a feeling of our aims, although the subject topic is different.
Copyright (c) 2020-2021, Leo Lahti; some rights reserved.
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Open positions
We are always looking for new group members with passion, talent, and grit!
PhD and Postdoc positions
If you are interested in working with us as a PhD student or postdoc, please send me an email. State briefly why you are interested and attach a CV, including information about the grades you had as an undergraduate. Important: please insert “Application PhD” or “Application Postdoc” in the subject line.
There are some postdoc scholarships available. I’d be happy to support you after you apply to our group. Take a look at the Marie Curie fellowship.
University of Turku master students
If you are a Master student in Turku, looking for a Master project, contact me (or any group member) by email or visit the office.
Bsc / Master students from elsewhere
If you are interested in pursuing a Master degree at University of Turku, see instructions from the university website. We can also take outstanding master students or summer interns.
Copyright (c) 2020-2021, Leo Lahti; some rights reserved.
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Publications / Leo Lahti
Publication material of our research group is collected in this folder.
- Presentation material in UTU Gitlab
- Some slides also available through SlideShare
Note that the copyrights may differ by publication.
Copyright (c) 2020-2021, Leo Lahti; some rights reserved.
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PhD student position / Project Researcher / Research Assistant
Open PhD student position / Project Researcher / Research Assistant in high-throughput biomedical data analysis (Finland / Belgium) 1.7.2017 – 30.6.2019
A position is open for a PhD candidate on high-throughput biomedical data analysis in the research team of Dr. Leo Lahti in University of Turku, Finland. The project provides a unique opportunity to gain widely applicable data analytical skills and make pioneering work in a rapidly emerging, data-intensive biomedical research area; a particular focus of the project is on computational analysis and modeling of the human microbiome and its individuality, dynamics, and function in large population cohorts. The project is funded by Academy of Finland and the preferred starting date is July 1, 2017.
Project The position is intended for full-time research including moderate contributions to university teaching and other supporting tasks. The project aims at a holistic characterization of the organization and dynamics of the human microbiome and its associations with host lifestyle and health, with the ultimate aim to improve fundamental understanding and applications of human biology and personalized medicine. A particular focus will be on the development of statistical techniques and data science tools for biomedical research, blending approaches from statistical machine learning, ecology, bioinformatics, and related fields. You will join the Turku biomedical research community and work in close collaboration with key partners in Finland and abroad. The project starts with a 6-12 month mobility period in the research group of Prof. Jeroen Raes at VIB/KU Leuven, Belgium.
Qualifications We are looking for outstanding candidates with a high level of independence as well as good collaboration skills and analytical capabilities. An ideal candidate would have a solid background in mathematics and/or statistics, familiarity with statistical programming (e.g. R/Python/Matlab/Julia) and bioinformatics, and ability to work in multidisciplinary environment. Fluent communication skills in English are essential. The doctoral candidate should hold a MSc degree in a relevant research field. Strong candidates who are willing to make MSc thesis as part of the project are also encouraged to apply. The new doctoral student must pass the standard enrollment process.
Salary The salary depends on the stage of the studies and is based on the University salary system for research personnel and will allow full-time focus on the doctoral studies. The position has a trial period of 4 months.
Host institute University of Turku is a world-class research university with an active biomedical research community. The research team of Dr. Lahti at the Department of Mathematics and Statistics focuses on the theory and applications of modern data analytics with a stimulating multidisciplinary research environment and international collaboration networks. The working language is English, and support for international staff is available. The project will start with a 6-12 month mobility period in the research group of Prof. Jeroen Raes at VIB/KU Leuven, Belgium. The city of Turku is a vivid, middle-sized student city with 180,000 inhabitants, beautiful natural surroundings and ample opportunities for free-time activities.
Application Applications must be submitted no later than Friday, May 26, 2017 via the electronic application form of the University of Turku. For further details, you can contact Dr Leo Lahti. Contact information and the link to the application system can be found from the University of Turku recruitment page (ID 3662).
Copyright (c) 2020-2021, Leo Lahti; some rights reserved.
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Tohtorikoulutettava / Projektitutkija / Tutkimusavustaja
Haetaan määräaikaiseen työsuhteeseen ajalle 1.7.2017 – 30.6.2019 jatko-opiskelijaa / projektitutkijaa / tutkimusavustajaa biolääketieteellisen data-analyysin alalla (Suomi / Belgia)
Jatko-opiskelupaikka biolääketieteellisen data-analyysin alalla on avoinna Dos. Leo Lahden tutkimusryhmässä (Turun yliopisto, Matematiikan ja tilastotieteen laitos). Hanke tarjoaa erinomaiset mahdollisuudet kartuttaa laajalti sovellettavia data-analyysivalmiuksia sekä uuden tutkimuksen tekemiseen nopeasti kasvavalla tutkimusalalla. Hanke keskittyy ihmiskehon mikrobiekosysteemien laskennalliseen mallitukseen. Rahoittajana on Suomen Akatemia. Suositeltu aloituspäivä on 1.7.2017.
Työnkuva Paikka on suunnattu täysipäiväiseen tutkimukseen ja jatko-opiskeluun ja sisältää tavanomaisen osallistumisen opetus- ja tutkimuksen tukitehtäviin. Hankkeen tavoitteena on muodostaa kokonaiskuvaa ihmiskehon mikrobiekosysteemien järjestäytymisestä, dynamiikasta, ja terveysvaikutuksista. Tuloksilla on perustutkimuksen lisäksi sovelluksia mm. henkilökohtaisessa lääketieteessä. Työtehtäviin kuuluu ensisijaisesti modernien tilastomenetelmien kehittäminen, jossa voidaan yhdistellä koneoppimisen, ekologian, bioinformatiikan, sekä muiden relevanttien tutkimusalojen lähestymistapoja. Hakijalla on mahdollisuus päästä mukaan Turun biolääketieteelliseen tutkimusyhteisöön ja työskennellä koti- ja ulkomaisten yhteistyökumppanien kanssa. Hanke alkaa 6-12 kuukauden liikkuvuusperiodilla VIB/KU Leuvenin yliopistossa Belgiassa professori Jeroen Raesin tutkimusryhmässä yhdessä Dos. Lahden kanssa.
Hakukriteerit Hyvän opintomenestyksen lisäksi hakijalta odotetaan itsenäisyyttä, hyvää yhteistyökykyä ja analyyttisiä valmiuksia. Hakijalla tulisi olla mainittavaa taustaa matemaattisissa/tilastotieteellisissä aineissa, kokemusta tilastollisesta ohjelmoinnista (esim R/Python/Matlab/Julia/tmv). Kokemus bioinformatiikasta katsotaan eduksi. Sujuva englanninkielen taito on tarpeen. Paikkaa voi hakea myös loppuvaiheen perustutkinto-opiskelija, joka on halukas tekemään aiheesta gradun ja jatkamaan tämän jälkeen jatko-opintoihin. Jatko-opiskelijaksi hakevan tulee täyttää tavanomaiset kriteerit ja läpäistä hakuprosessi.
Palkka Palkkataso riippuu opiskeluvaiheesta ja perustuu yliopiston yleiseen palkkausjärjestelmään. Palkka mahdollistaa täysipäiväisen jatko-opiskelun. Koeaika on 4 kuukautta.
Suorituspaikka Turun yliopisto on kansainvälinen tutkimusyliopisto, jossa on aktiivinen biolääketieteen tutkijayhteisö. Dos. Lahden tutkimusryhmä Matematiikan ja tilastotieteen laitoksella keskittyy modernin data-analyysin teoriaan ja sovelluksiin monitieteisessä tutkimusympäristössä. Työskentelykielenä ovat Suomi ja Englanti. Hanke alkaa 6-12 kuukauden liikkuvuusjaksolla Prof. Jeroen Raesin tutkimusryhmässä VIB/KU Leuvenin yliopistossa Belgiassa.
Hakuohjeet Haun takaraja on 26.5.2017. Lisätietoja Dos. Lahdelta. Tarkemmat tiedot ja linkki hakulomakkeeseen löytyvät Turun yliopiston rekrytointijärjestelmästä (ID 3662).
Copyright (c) 2020-2021, Leo Lahti; some rights reserved.
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Publications by theme:
Funding and support
The work has been supported by:
- EU / Horizon
- Academy of Finland
- Strategic Research Council in Finland
- KONE foundation
- Alhopuro foundation
- Finnish Cultural FOundation
- Turku University Foundation
- Biocity Turku
- CIMO/EFUDI
- UTUGS/MATTI and UTUGS/DPT Graduate Schools
- University of Turku
Projects
Links to ongoing and recent projects.
Computational life sciences:
- Eco-evolutionary mechanisms underlying critical transitions in microbial communities Academy of Finland 2020-2024
- FindingPheno EU / Horizon 2021-2025 for computational multi-omics
- ML4microbiome COST action on Statistical and Machine Learning Techniques in Human Microbiome Studies; EU 2019-2023
- KONE / HAT research to compare evolutionary processes in nature and society (2022-2024)
- Biocity Turku Computational and Molecular Methods for Life Sciences (CompLifeSci) program (lead; 2022-2026)
Computational humanities:
- Digital History for Literature in Finland Academy of Finland; lead 2022-2026
- OpenMuse EU / Horizon 2023-2025
- OpenMUSE/RIA EU / Horizon 2023-2025
- Strategic Research Council: Young Despair 2022-2025
- FIN-CLARIAH Infrastructure for Digital Humanities
Copyright (c) 2020-2021, Leo Lahti; some rights reserved.
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-https://orcid.org/0000-0001-5537-637X
Postdocs
Matti Ruuskanen
Microbial ecology, bioinformatics, human microbiomes, environmental change.
Guilhem Sommeria-Klein
Microbial ecology and biogeography, statistical ecology, probabilistic modeling.
Pande Putu Erawijantari
Human microbiome, metagenomic, metabolomic, microbial ecology, bioinformatics
Aura Raulo
Microbiomes, ecology.
Katariina Pärnänen
Metagenomics, bioinformatics, AMR.
Ville Laitinen
Probabilistic modeling, time series, early warning signals.
PhD researchers
Moein Khalighi
Ecological Memory, Fractional Calculus, Differential Equations, Dynamic Modelling, Data Analysis.
Chandler Ross
Eco-Evolutionary Dynamics, Statistical Modelling, Time Series.
Tuomas Borman
Bioinformatics, Human microbiome, R package development.
Shivang Pravin Bhanushali
Metagenomics, Antimicrobial Resistance, Human microbiome, Bioinformatics
Renuka Potbhare @@ -19,15 +18,4 @@
Chouaib Benchraka
Machine Learning, data science.
Giulio Benedetti
Data Science.
Akewak Jeba
Data Analytics, Data science
Julia Matveeva
Computational History, Digital Humanities
Alumni
Postdocs:
- Rajesh Shigdel (visiting scholar, 2022)
Co-supervised PhDs:
- Iiro Tiihonen
- Ville Vaara
- Henrik Eckerman
- Mrunalini Lotankar
- Anna Sorjamaa
- Asiye Kazeroonian
Visiting scholars:
- prof. Dhiraj Dhotre (2023; visiting professor)
- Renuka Potbhare (2023; visiting researcher)
- Dattatray Mongad (2022; visiting researcher)
Research assistants & interns:
- Teo Dallier (2023; summer intern)
- Elliot Gaudron-Parry (2023; summer intern)
- Inès Benseddik (2023; summer intern)
- Basil Courbayre Dussau (2023; summer intern)
- Elina Chiesa (2023; intern)
- Kevin Gatel (2022; summer intern)
- Malaury Martin (2022; summer intern)
- Yagmur Simsek (2021-2022)
- Julia Matveeva (2021)
- Tom Gobardhan (2021; summer intern)
- Tim Garrels (2020; BARI internship)
- Binu Mathew (2019-2020)
- Hege Roivainen (2016-2020; at Helsinki Computational History Group)
- Aaro Salosensaari (2019-2020)
- Prashant Gaikwad (2019; SPARC / supported by Government of India)
MSc students:
- Marija Rakic (2023; Erasmus)
- Dorde Klisura (2022; Erasmus)
- Anastasia Karavaeva (2020)
- Wisam Saleem (2019-2020)
- Binu Mathew (2019-2022)
Copyright (c) 2020-2021, Leo Lahti; some rights reserved.
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