Dr. Andrew Torda

Professor

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Biography

Andrew Torda is a prominent researcher in the field of biomolecular modeling and bioinformatics. He leads a research group at the University of Hamburg, where he specializes in low-resolution force fields, protein structure prediction, protein threading, and methodologies for optimizing protein sequences. Torda's academic journey began in the Netherlands from 1988 to 1990, followed by a significant tenure at ETH Zurich for five years. In 1995, he became a group leader at the Research School of Chemistry at the Australian National University, before moving to Hamburg in October 2002. Throughout his career, Torda has contributed to the understanding of protein sequence structure alignment and has developed scoring functions to aid in the optimization of amino acid substitution matrices. His work has been foundational in advancing techniques for free energy estimation and sequence optimization, with a focus on model systems and the methods used in protein structure prediction. He is actively involved in teaching and has collected valuable student software projects, enhancing the learning experience within his group.

Research Interests

Experience

Head Research Group

2002-10-01 — Present

University of Hamburg • Hamburg, Germany

Leading a research group focused on biomolecular modeling and bioinformatics.

Requirements for University of Hamburg

Master Program
Requirements
GPA Requirement
Required:2.5
IELTS
Listening
Required:6
Reading
Required:6
Writing
Required:6
Speaking
Required:6
Overall
Required:6.5
TOEFL
Listening
Required:20
Reading
Required:20
Writing
Required:20
Speaking
Required:20
Total
Required:90
Prerequisites
Bachelor's degree in Computer Science or related field At least 60 ECTS in core computer science subjects
Application Checklist
  • Transcript of Records
  • Bachelor's degree certificate (or preliminary transcript)
  • Proof of English proficiency
  • Curriculum Vitae
  • Letter of Motivation
  • Module descriptions/table of 60 ECTS in CS
Specialization Notes

Includes tracks like Intelligent Adaptive Systems (IAS).