プロフィール詳細

プロジェクトを作成

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Mikkel S.に依頼

Switzerland

Data Science | PhD in Neuroscience

プロフィール概要

Experienced Data Scientist & Neuroscience PhD | Expert in Machine Learning, Statistical Analysis, Scientific Writing, and Research Consulting

専門分野

• ☆ Neuroscience
• ☆ Computational Neuroscience
• ☆ Cognitive Neuroscience
• ☆ Systems Neuroscience
• ☆ Data Analysis
• ☆ Predictive Modeling & Analytics
• ☆ Data Processing
• ☆ Data Exploration
• ☆ Cluster Analysis
• ☆ Data Visualization
• ☆ Big Data Analytics
• ☆ Data Collection
• ☆ Data Management
• ☆ Data Manipulation
• ☆ Machine Learning
• ☆ Data Cleaning
• ☆ Neural Networks
• ☆ Artificial Intelligence
• ☆ Deep Learning
• ☆ Statistics
• ☆ Applied Statistics
• ☆ Meta-Analysis
• ☆ Regression Analysis
• ☆ Multivariate Analysis
• ☆ Nonlinear Regression
• ☆ Bayesian Statistics
• ☆ Correlation Analysis
• ☆ Survey Design
• ☆ Study Design
• ☆ Medical Statistics
• ☆ Health Data Analysis
• ☆ Data Storage
• ☆ Human Behavior & Psychology
• ☆ Cognitive Science
• ☆ Clinical Psychology
• ☆ Python
• ☆ SPSS
• ☆ Matlab
• ☆ SQL
• ☆ Excel
• ☆ LaTex
• ☆ R
• ☆ Scikit-learn
• ☆ Markup Languages
• ☆ Medical Imaging/Radiology
• ☆ Psychiatry
• ☆ Magnetic Resonance Imaging (MRI)
• ☆ Neuroradiology
• ☆ Hypothesis
• ☆ Peer Review
• ☆ Research Methodology
• ☆ Survey Design & Methodology
• ☆ Fact Checking
• ☆ Literature Search
• ☆ Photography & Image Editing
• ☆ Technical & Scientific Writing
• ☆ Manuscript & Journal Article Writing
• ☆ Instructional Materials
• ☆ Release Notes
• ☆ Textbook Content Writing
• ☆ Science Communication
• ☆ Literature Review
• ☆ Traditional/Narrative Literature Review
• ☆ Systematic Literature Review
• ☆ Scientific Proofreading & Editing
• ☆ Proofreading & Editing
• ☆ Language Translation
• ☆ Course Content Writing

サービス

• Writing
• Research
• Consulting
• Data & AI

Writing Technical Writing, General Proofreading & Editing, Translation

Research Scientific and Technical Research, Systematic Literature Review

Consulting Scientific and Technical Consulting

Data & AI Predictive Modeling, Statistical Analysis, Data Visualization, Big Data Analytics, Data Cleaning, Data Processing, Data Insights

職務経験

Researcher & Doctoral Candidate

Centre Hospitalier Universitaire Vaudois Département d'oncologie

2月 2021 - 6月 2025

Working Student

Merantix AG

4月 2019 - 6月 2019

Research Intern

Free University of Berlin

2月 2019 - 4月 2019

Statistics Tutor

University of Bremen

4月 2017 - 7月 2017

学歴

Doctor of Philosophy (PhD) (Radiology)

University of Lausanne

2月 2021 - 6月 2025

Master of Science (MSc)

Philipps University of Marburg

10月 2018 - 11月 2020

Bachelor of Science (BSc) (Psychology)

University of Bremen

10月 2015 - 10月 2018

認定資格

• RiceX355.1: RiceX Linear Algebra Part 1

  RICEx

  https://courses.edx.org/certificates/053cb3e05f024c5e990b8afdae935a6f

  3月 2021 - 現在

出版物

JOURNAL ARTICLE

Jagruti Patel, Mikkel Schöttner, Anjali Tarun, Sebastien Tourbier, Yasser Alemán-Gómez, Patric Hagmann, Thomas A. W. Bolton (2024). Modeling the impact of MRI acquisition bias on structural connectomes: Harmonizing structural connectomes . Network Neuroscience.

S. Vieira, T. A. W. Bolton, M. Schöttner, L. Baecker, A. Marquand, A. Mechelli, P. Hagmann (2024). Multivariate brain-behaviour associations in psychiatric disorders . Translational Psychiatry.

Sebastien Tourbier, Joan Rue-Queralt, Katharina Glomb, Yasser Aleman-Gomez, Emeline Mullier, Alessandra Griffa, Mikkel Schöttner, Jonathan Wirsich, M. Anıl Tuncel, Jakub Jancovic, et al. (2022). Connectome Mapper 3: A Flexible and Open-Source Pipeline Software for Multiscale Multimodal Human Connectome Mapping . Journal of Open Source Software.

PREPRINT

Mikkel Schöttner, Sandra Vieira (2024). The Multi-Dimensional Structure of Psychotic Disorders .

Bruno Hebling Vieira, Mikkel Schöttner, Vince D Calhoun, Carlos Ernesto Garrido Salmon (2024). Beyond functional connectivity: deep learning applied to resting-state fMRI time series in the prediction of 58 human traits in the HCP .

Céline Provins, Mikkel Schöttner, Michael Dayan, Vivi Nastase, Jenny Lunde, Oriol Mãne Benach, Eilidh MacNicol, Elodie Savary, Saren H. Seeley, McKenzie Paige Hagen, et al. (2023). Signal-to-noise ratio estimates predict head motion presence in T1-weighted MRI .

Exploring the Latent Structure of Behavior Using the Human Connectome Project’s Data <head> <META HTTP-EQUIV="Refresh" CONTENT="0;URL=/servlet/useragent"> </head> .

CONFERENCE POSTER

Schöttner, Mikkel and Bolton, Thomas A. W. and Patel, Jagruti and Tarun, Anjali and Hagmann, Patric(2022). Domains of Behavior and Psychopathology Derived via Factor Analysis . OHBM 2022. figshare