diff --git a/pynxtools_mpes/igor.py b/pynxtools_mpes/igor.py
new file mode 100644
index 0000000..4fa25fc
--- /dev/null
+++ b/pynxtools_mpes/igor.py
@@ -0,0 +1,164 @@
+"""
+Parser for the igor binarywave files from the FHI Phoibos detector
+"""
+import re
+from bisect import insort
+from typing import Any, Dict, List
+
+import numpy as np
+from igor2 import binarywave
+
+
+def parse_note(bnote: bytes) -> Dict[str, Any]:
+    """
+    Parsers the note field of the igor binarywave file.
+    It assumes that the note field contains key-value pairs of the
+    form 'key=value' separated by newlines.
+
+    Args:
+        bnote (bytes): The bytes of the binarywave note field.
+
+    Returns:
+        Dict[str, Any]: The dictionary of the parsed note field.
+    """
+    note = bnote.decode("utf-8").replace("\r", "\n")
+    notes = {}
+    for line in note.split():
+        split = line.split("=")
+        if len(split) == 2:
+            key, val = split
+            notes[key] = val
+
+    return notes
+
+
+def sort_key(filename: str, pattern: str = r"[^\/_]+_(\d+)_(\d+).ibw$") -> int:
+    r"""
+    Returns the sort key based on the second group in the regex pattern.
+    Default is to match filenames of the form ..._<scan>_<frame>.ibw.
+    Where <frame> is used as the sort key.
+
+    Args:
+        filename (str): The filename to return a sort key for.
+        pattern (str, optional):
+            The sort key pattern. Defaults to r"[^\/_]+_(\d+)_(\d+).ibw$".
+
+    Raises:
+        ValueError: If no match in the filename is found.
+
+    Returns:
+        int: The sort key.
+    """
+    groups = re.search(pattern, filename)
+    if groups is not None:
+        return int(groups.group(2))
+    raise ValueError(
+        "Invalid filename: Expected file of the form ..._<scan>_<frame>.ibw."
+    )
+
+
+def find_scan_sets(
+    filenames: List[str], pattern: str = r"[^\/_]+_(\d+)_(\d+).ibw$"
+) -> Dict[int, Any]:
+    r"""
+    Returns a dict of scan sets where the key is the scan number
+    and the value is a list of filenames.
+    Default is to match filenames of the form ..._<scan>_<frame>.ibw.
+    Where <frame> is used as the sort key and <scan> is used to indicate the scan number.
+
+    Args:
+        filenames (List[str]): _description_
+        pattern (str, optional): _description_. Defaults to r"[^\/_]+_(\d+)_(\d+).ibw$".
+
+    Returns:
+        Dict[int, Any]: _description_
+    """
+    scan_sets: Dict[int, Any] = {}
+    for fn in filenames:
+        groups = re.search(pattern, fn)
+        if groups is not None:
+            scan = int(groups.group(1))
+            if scan not in scan_sets:
+                scan_sets[scan] = []
+            insort(scan_sets[scan], fn, key=lambda fn: sort_key(fn, pattern))
+    return scan_sets
+
+
+def axis_from(ibw_data: Dict[str, Any], dim: int) -> np.ndarray:
+    """
+    Returns the axis values for a given dimension from the wave header.
+
+    Args:
+        ibw_data (Dict[str, Any]): The ibw data containing the wave_header.
+        dim (int): The dimension to return the axis for.
+
+    Returns:
+        np.ndarray: The axis values.
+    """
+    wave_header = ibw_data["wave"]["wave_header"]
+    return (
+        wave_header["sfA"][dim] * np.arange(wave_header["nDim"][dim])
+        + wave_header["sfB"][dim]
+    )
+
+
+def axis_units_from(ibw_data: Dict[str, Any], dim: int) -> str:
+    """ "
+    Returns the unit for a given dimension from the wave header.
+
+    Args:
+        ibw_data (Dict[str, Any]): The ibw data containing the wave_header.
+        dim (int): The dimension to return the unit for.
+
+    Returns:
+        str: The axis units
+    """
+    unit_arr = ibw_data["wave"]["wave_header"]["dimUnits"][dim]
+
+    unit = ""
+    for elem in unit_arr:
+        unit += elem.decode("utf-8")
+
+    return unit
+
+
+def read_ibw(filenames: List[str]) -> Dict[str, Any]:
+    """
+    Reads the igor binarywave files and returns a dictionary containing the data.
+
+    Args:
+        filenames (List[str]): The filenames to read.
+
+    Returns:
+        Dict[str, Any]: The dictionary containing the data.
+    """
+    template: Dict[str, Any] = {}
+    for scan_no, files in find_scan_sets(filenames).items():
+        waves = []
+        beta = []
+        theta = []
+        for file in files:
+            ibw = binarywave.load(file)
+            notes = parse_note(ibw["note"])
+            beta.append(float(notes["Beta"]))
+            theta.append(float(notes["Theta"]))
+            waves.append(ibw["wave"]["wData"])
+
+        data_entry = f"/ENTRY[entry{scan_no}]/data"
+        template[f"/ENTRY[entry{scan_no}]/theta"] = theta
+        template[
+            f"/ENTRY[entry{scan_no}]/PROCESS[process]/energy_referencing/reference_peak"
+        ] = "vacuum level"
+        template[f"{data_entry}/@axes"] = ["theta", "beta", "energy"]
+        template[f"{data_entry}/AXISNAME[beta]"] = beta
+        template[f"{data_entry}/AXISNAME[beta]/@units"] = "degrees"
+        template[f"{data_entry}/AXISNAME[energy]"] = axis_from(ibw, 0)
+        template[f"{data_entry}/AXISNAME[energy]/@units"] = axis_units_from(ibw, 0)
+        template[f"{data_entry}/AXISNAME[theta]"] = axis_from(ibw, 1)
+        template[f"{data_entry}/AXISNAME[theta]/@units"] = axis_units_from(ibw, 1)
+        template[f"{data_entry}/@signal"] = "data"
+        template[f"{data_entry}/data"] = np.array(waves).swapaxes(1, 2).swapaxes(0, 1)
+        template[f"{data_entry}/data/@units"] = "counts"
+        template[f"{data_entry}/energy/@type"] = "kinetic"
+
+    return template
diff --git a/pyproject.toml b/pyproject.toml
index 121e4b2..d69b847 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -42,6 +42,9 @@ dev = [
     "types-pyyaml",
     "pip-tools",
 ]
+igor = [
+    "igor2",
+]
 
 [project.entry-points."pynxtools.reader"]
 mpes = "pynxtools_mpes.reader:MPESReader"